Download:
pdf |
pdfVoice of the Veteran Line of Business Tracking Study
Compensation Service
Fiscal Year 2015 Non-Response Bias Analysis
VETERANS BENEFITS ADMINISTRATION
[FY15 REPORT]
Table of Contents
Executive Summary .................................................................................................................................. 4
Introduction ............................................................................................................................................. 5
Methodology ............................................................................................................................................ 6
2.1 J.D. Power Index Model ................................................................................................................... 6
2.2 Sampling......................................................................................................................................... 10
2.3 Data Collection ............................................................................................................................... 10
Non-Response Bias Analysis................................................................................................................... 11
3.1 Survey Yield .................................................................................................................................... 20
3.2 Missing Data Patterns and Mechanisms ........................................................................................ 27
3.3 Margin of Error .............................................................................................................................. 28
3.3.1 Sampling Distribution ....................................................................................................... 29
3.3.2 Distribution of Overall Satisfaction Index Scores.............................................................. 30
3.3.3 Analysis for Demographic Differences .............................................................................. 31
3.3.4 Data Imputation Analysis for Demographic Differences .................................................. 37
Findings .................................................................................................................................................. 40
Conclusion .............................................................................................................................................. 41
References ............................................................................................................................................. 42
List of Appendices
Appendix A Missing Data Patterns and Mechanisms .................................................................... 43
Appendix B Item Response Rates .................................................................................................. 45
Appendix C Study Overview ........................................................................................................... 49
1.1 Study Background .................................................................................................................. 49
1.2 Methodology ......................................................................................................................... 49
1.2.1 Sample Criteria .................................................................................................................... 50
1.2.2 Sample File Generation ................................................................................................... 50
1.2.3 Data Transfer .................................................................................................................... 51
1.2.4 Data Cleaning .................................................................................................................... 53
1.2.5 Sample Cleaning Rules Glossary..................................................................................... 53
1.2.6 Sample Selection .............................................................................................................. 54
1.2.7 Fielding/Sampling Frequency ......................................................................................... 54
1.2.8 Order Generation and Fulfillment Process ................................................................... 54
1.2.9 Data Collection ................................................................................................................. 56
1.2.10 Reporting......................................................................................................................... 56
ii
Appendix D .................................................................................................................................... 57
Approaches to Mitigating the Effect of Non-Response Bias .......................................................... 57
1.1 Approach 1: Strategies to Maximize Response Rates ........................................................... 57
1.2 Approach 2: Correcting Unit Non-response Bias with Sample Weighting and Survey Raking58
Strategies to Improve Response Rate ............................................................................................ 59
Appendix E Impact of FAR 8.8 ........................................................................................................ 60
1.1 Impact .................................................................................................................................... 60
Appendix F Survey Questionnaire.................................................................................................. 61
Appendix G List of Acronyms………………………………………………………………..………….……………………….78
iii
Executive Summary
The Voice of the Veteran (VOV) Line of Business Tracking Satisfaction Research Study was
developed to establish continuous satisfaction measurement and incorporate direct Veteran
feedback in the decision making process in order to improve the level of service to
Servicemembers, Veterans, and their beneficiaries.
As part of this study, two surveys were fielded in Fiscal Year 2015 (FY15) for the Department of
Veterans Affairs (VA), Veterans’ Benefits Administration (VBA) Compensation Service. One
survey was based upon the access of the benefit and the other on the ongoing servicing of the
benefit. The Access survey yielded a response rate of 21.96% (2.55% increase from FY14) and
the Servicing survey yielded a response rate of 25.03% (3.64% increase from FY14). These rates
were lower than the estimated response rate submitted with the information collection request
(ICR) as well as lower than the Office of Management and Budget’s standard of 80% (at the
overall unit response rate).
OMB’s “Standards and Guidelines for Statistical Surveys,” Section 3.2, Guideline 3.2.9, notes
that a non-response analysis should be conducted for surveys with an overall unit response rate
of less than 80%. Therefore, J.D. Power (JDP) conducted the necessary statistical tests in
accordance with OMB’s guidelines in order to verify the validity of Compensation’s Service’s
survey results for FY15.
The initial 2015 analyses for these reports were done in consultation with Dr. Don Dillman, a
professor at Washington State University. Dr. Dillman is regarded as a key survey method
expert on non-response bias research and the report conforms to sound statistical research
practices in accordance with OMB standards. The analysis performed also includes an iterative
survey raking procedure to derive sample weightings based on a simultaneous balancing
analysis of the demographic differences.
After adjusting for demographic differences between survey respondents and nonrespondents, the statistical tests performed on the survey responses for the Compensation
Service surveys collected, illustrate that no differences were found in the Overall Satisfaction
Index Score and Advocacy rating (likelihood to inform others about VA benefits).
The sample for the Access population was defined as individuals who have received a decision
in the past 30 days and includes those who were found eligible on a new or subsequent claim
and those who have been denied and are not appealing the decision. The Access Overall
Satisfaction score (663) and advocacy rating (3.53 on rating 1-4) are not impacted in any
meaningful way by non-response bias.
The sample for the Servicing population was defined as individuals who began receiving
compensation benefits within the last six to eighteen months. The Servicing Overall Satisfaction
score (630) and advocacy rating (3.50 on rating 1-4) are not impacted by non-response bias.
This analysis confirms that the data collected during Fiscal Year 2015 is valid for use by VBA.
4
Introduction
In an effort to achieve the highest level customer service, VBA partnered with J.D. Power to
conduct Veteran satisfaction research on its behalf. VBA’s Voice of the Veteran (VOV)
Satisfaction Initiative was established to continuously measure and improve the level of service
to Servicemembers, Veterans, and their beneficiaries.
The intent of this initiative is to:
Reinstate VBA’s customer satisfaction research program in order to incorporate Veteran
feedback into the decision-making process
Identify the critical factors to Veterans’ satisfaction with benefits and services provided
by VBA
Provide continuous feedback to validate effectiveness of new initiatives and process
changes
Provide decision-makers and stakeholders with timely and actionable feedback on a
continuous basis
Identify and document best practices, and act as a vehicle to celebrate successful
interactions and experiences
The VOV Line of Business Tracking Satisfaction Research Study was developed to continuously
field customer satisfaction survey instruments to provide Veteran and beneficiary feedback on
the following VBA lines of business and benefit programs: Compensation, Pension, Education,
Vocational Rehabilitation and Employment, and Loan Guaranty (including Specially Adapted
Housing). In support of this effort, in FY15, JDP fielded a survey instrument regarding the Access
and Servicing process on behalf of the Compensation program. The purpose of the Access and
Servicing process surveys was to identify the factors critical to Veteran satisfaction with the
access and receipt of benefits issued by VBA and to improve the level of services provided.
The survey instruments for Servicing and the Access process were developed in collaboration
with VA’s Compensation Service, and in accordance with OMB’s guidelines concerning
statistical collection procedures and methods. After the initial survey instrument was designed,
cognitive labs using the “think aloud” method were conducted to evaluate user experience
when completing the survey. Prior to the FY15 fielding of the Servicing and Access process
survey, a benchmark pilot study was conducted from October 2012 through January 2013 to
further assess the effectiveness of the methodology and conformance to OMB’s standards.
Additionally, we have also fielded the study in 2014 and the 2015 fielding will be the third
iteration.
5
Methodology
2.1 J.D. Power Index Model
J.D. Power defines customer satisfaction as a measure of how well product or service
experiences fit the expectations of customers. All JDP index models assume a two-tiered
regression model involving factors and attributes. Each customer experience is influenced by
several factors (i.e. first tier), which in turn, are influenced by several attributes or drivers (i.e.
second tier). A diagram of the index model follows on the subsequent page.
In order to begin the index model calculation, each set of attributes within a factor is used to
predict the Overall Satisfaction Index score (sub-OSAT) for that factor. An importance weight is
assigned to each attribute, where the weight of “importance” of each attribute is defined as the
ability of that attribute to predict Overall Satisfaction. A multiple regression model is used to
estimate the attribute weights. This model produces the “bottom” level weights and is
computed for each factor separately. The bottom level weights are rescaled so that they add up
to a rating of 1 point within each subcategory. As a result, the percentage of total explained
variation in the sub-OSAT that is due to a particular attribute constitutes that attribute’s
importance weight within its respective factor.
Following the calculation of attribute (i.e. bottom level) weights, the factor (i.e. top-level)
weights are calculated. Factor scores are calculated by taking the sum of the product of the
attribute rating scores and the attribute importance weights. This model produces the “top”
level weights and these weights are rescaled so that they add up to a score of 1 point. Thus, the
percentage of the total explained variation in the Overall Satisfaction Index score that is due to
a particular sub-OSAT constitutes that factor’s importance weight.
After all factor scores are computed, they are weighted so that some contribute more to
Overall Satisfaction than others, based on the index importance weights. The index score is
subsequently calculated by taking the sum of the product of all of the factor scores and the
factor importance weights. Finally, both the index and factor scores are multiplied by 100 so
that the range of each is 100 (if all attributes were rated 1 point) to 1,000 (if all attributes were
rated 10 points).
By applying the importance weights derived from the two-tiered modeling approach, JDP
creates a weighted index score that ranges from a low of 100 to a high of 1,000 points. This
index approach has the benefit of being highly reliable and valid and provides increased ability
to discriminate the performance levels of companies and organizations.
6
Compensation Access and Servicing Process Index Weights
In working with Compensation’s subject matter experts and leadership, the design of its survey
encompasses the factors and attributes as outlined in the tables on the next page. The factors
(Benefit Information, Contact with VA, Benefit Application, and Benefit Entitlement) and
attributes (Ease of Accessing Information, Availability of Information, etc.) represent Access and
Servicing Index Models in FY15. The corresponding weights for each factor and attribute are the
weights based on the above index model calculation. The weights are derived from the relative
importance of each factor or attribute to the respondents.
7
Table 2.0. Access: Index Model Weights
Access Index Model Weights
Effective
Weight
Benefit Information
Contact with VA
Application Process
Clarity of Info on Appeal
Benefit Entitlement
18.28%
11.23%
31.18%
2.88%
36.43%
Table 2.1. Access: Weights by Attribute
Access Weights by Attribute
Effective
Weight
Benefit Information
Ease of accessing information
3.88%
Availability of information
2.67%
Clarity of information
3.20%
Usefulness of information
3.52%
Frequency of information
5.02%
Application Process
Ease of completing the application
7.75%
Timeliness of eligibility notification
13.31%
Flexibility of application methods
10.12%
Contact with VA
11.23%
Clarity of Info on Appeal
2.88%
Benefit Entitlement (Timeliness of
receiving benefit)
36.43%
8
Table 2.2. Servicing: Index Model Weights
Servicing Index Model Weights
Effective
Weight
Benefit Information
Contact with VA
Benefit Entitlement
26.49%
12.49%
61.02%
Table 2.3. Servicing: Weights by Attribute
Servicing Weights by Attribute
Effective
Weight
Benefit Information
Ease of accessing information
5.17%
Availability of information
3.22%
Clarity of information
4.41%
Usefulness of information
6.23%
Frequency of Information
7.46%
Benefit Entitlement
Disability evaluation rating
percentage
26.96%
Timeliness of receiving
benefit/services
14.59%
Clarity of your disability rating
19.47%
Contact with VA
12.49%
9
2.2 Sampling
The Servicing survey was fielded to Veterans and beneficiaries who began receiving
compensation benefits six to eighteen months ago. The Access survey is fielded to Veterans
and beneficiaries who received a decision for their application for compensation benefits within
the past 30 days. These individuals may include those who were found eligible on a new or
subsequent claim and those who have been denied and are not appealing the decision.
J.D. Power mailed approximately 160,000 surveys for the Access survey and 60,000 for the
Servicing survey to Veterans (and surviving spouses) across the nation in FY15. The target
number of completed surveys was 48,000 for Access and 18,000 for Servicing. The actual
number of completed surveys received for Access was 36,605 and for Servicing it was 16,030.
The samples used in this study was provided by the Office of Performance Analysis and Integrity
(PA&I) on behalf of Compensation and delivered to JDP. The sample was a random sample from
the available records provided in the sample file. See Appendix D, Sample Plan Overview for
further detail on sampling.
Methodology
Fielding Frequency
Total Mail-outs in
FY15
Access
Mixed
Monthly
160,000
Servicing
Mixed
Annually
60,000
Survey Instrument
2.3 Data Collection
During the survey fielding period, both self-administered online survey returns and selfadministered paper surveys were collected. While verbatim responses are recorded by a live
survey processor, responses from paper surveys are scanned through automated imaging
software. Survey returns undergo quality assurance to validate the accuracy of responses
captured.
Respondents received two separate mailings, and had the option of completing the survey on
paper or online:
1st Mailing: Postcard, introducing the study to the respondent, which included an online
survey link and a unique access code login for the online survey.
2nd Mailing: Survey Package, which included a cover letter with the online survey link, a
paper survey, and a business reply envelope.
10
Each time the surveys were deployed, the survey packages were subject to a proof approval
process that utilized three levels of approvals by J.D. Power, Benefits Assistance Service (BAS),
and VA Publications Services Division (VAPSD). After the print vendor mailed the postcards and
survey packages, mail receipts were sent to VBA.
During the survey fielding period, JDP provided a toll-free survey hotline and dedicated e-mail
address to answer survey-related inquiries and to provide assistance to respondents for
completing the surveys. The telephone and e-mail helpdesk was staffed with three JDP
employees who answered inquiries during regular business hours (8:00am-5:00pm PST,
Monday thru Friday). A voice message system was available to receive phone messages so
after-hours calls could be responded to the following business day. An automatically generated
e-mail response was sent to all e-mail inquiries informing respondents that their e-mail was
received and they would receive a response within 24 hours. JDP helpdesk representatives
logged each survey-related inquiry in a password protected spreadsheet documenting the
reason for the inquiry, the resolution provided, and the contact information of each caller. At
the end of each month, a log containing all inquiries was provided to the Contracting Officer
Representative (COR) for review. If non-survey related high-severity benefit inquiries were
received, J.D. Power contacted the COR immediately with the respondent’s contact
information.
Throughout the course of the program, weekly status meetings were held between JDP and
BAS to discuss survey administration. Biweekly status meetings were held between the
Government Printing Office print vendor, JDP, BAS and VAPSD to discuss the printing and
mailing of the survey materials.
Non-Response Bias Analysis
The purpose of the non-response bias analysis is to ascertain the possible causes of variance in
response rates among different respondent demographics and/or determine if any bias has
been introduced with a low response rate. Given that the Voice of the Veteran Compensation
Access survey had an overall unit response rate of approximately 22% and the Voice of the
Veteran Compensation Servicing survey had an overall unit response rate of 25% in FY15, the
following section examines whether a low response rate or other factors may have caused
respondent bias to occur.
The Office of Management and Budget’s Questions and Answers, “When Designing Surveys for
Information Collections” dated January 2006, and “Standards and Guidelines for Statistical
Surveys” dated September 2006 (see References) provide guidelines on acceptable survey
design and response rates. OMB guidelines recommend a non-response bias evaluation for
surveys with an overall unit response rate of less than 80%.
In addition to the above referenced documents prepared by OMB, J.D. Power assessed other
source documents that were written and published by the Federal Committee on Statistical
Methodology, “Statistical Policy Working Paper 17, Survey Coverage” (1990) and “Statistical
Policy Working Paper 31, Measuring and Reporting Sources of Error in Surveys” (2001).
11
While high response rates are always desirable in surveys, JDP finds an 80% response rate is not
achievable for most voluntary, satisfaction-based, survey research studies (Malhotra & Birks,
2007). In particular, survey research studies that do not provide an incentive are subject to not
achieving an 80% response rate. To better illustrate this point, the Dillman Method for survey
fielding was discussed in Dillman, D. A. (2014, pp. 22), detailing the efforts to attain an 80%
response rate.
A survey instrument was fielded to 600 students at the University of Washington, the same
institution that sponsored the study. After five attempts to solicit a response in a closed
university setting, as well as offering a monetary incentive to complete the study, the 80%
response rate was not achieved and instead garnered only a 77% response rate. The JDP team
met with the VA Contracting officer Representative to discuss current trends and realistic
response rates. As noted JDP does not believe that an 80% response rate is achievable and this
concern was shared with the Benefits Assistance Service team.
JDP conducted the following non-response bias analysis to determine if the respondents (i.e.
those who completed the survey) were different in a meaningful way from the nonrespondents (i.e. those who were sent a survey, but did not complete it). Chi-squared analyses
consist of comparisons between respondents and non-respondents on available demographic
variables such as gender, age, race, geographical region, war participation (service era), and
military service branch. The U.S. states were converted to standard USA census regions
(Midwest, Northeast, South, and West) in order to aggregate the data and enhance regional
comparisons.
J.D. Power research indicates that there is an absence of systematic statistical differences of
respondents’ overall satisfaction on the mail and online survey results. Research does suggest
differences can occur between mixed mode survey methodologies (mail, online, and phone),
but these are primarily related to (a) social desirability and interviewer bias associated with
phone surveys (see Baum, Chandonnet, Fentress, and Rasinowich, 2012, p. 2, for a review) and
(b) that older respondents tend to respond by mail more often than online.
The non-response bias analysis was conducted across both mail and online survey collection
modes. However, as a verification check, we examined potential differences in mail vs. online
survey responses by utilizing a t-test analysis on the OSAT index and advocacy rating which
serve as measures of Veterans’ overall satisfaction and benefits advocacy. The overall
satisfaction index is defined in the Methodology section of this report. The advocacy rating is
defined as Veterans’ likelihood to inform others about VA benefits.
12
Throughout this report, we are conducting statistical analyses to compare survey respondents
and non-respondents. Frequently used statistical tests can include the T-Test, Chi-Square, or
Analyses of Variance (ANOVA). These tests generate relevant t-statistics, Chi-Squares, or F
statistics that are reported. The magnitude of the statistic’s value (either positive or negative)
measures the size of the difference relative to the variation in the data. If the statistic is not
large enough to generate a probability (p-value) less than .05, then it falls below the accepted
standard probability cut-off level that indicates whether a statistical difference is significant. If
a difference is not significant, statisticians regard these results as part of the normal sample
variation that occurs within the same population. Throughout this report, the probability pvalue standard of “must be less than .05 to be significant” is used for all statistics reported.
Table 3a.e shows there were statistical differences found for Compensation Access between
the mail and online methodologies on both Overall Satisfaction and Advocacy. The results
show that satisfaction was higher for mail respondents whereas advocacy was higher for online
respondents.
Table 3a.e. Access: T-Test Analysis of Mail vs. Online Survey Results
Rating Measure
Overall Satisfaction Index (100 - 1000
range)
Likelihood to inform others about VA
benefits (rating 1 - 4)
Mail
Online
t-statistic
p-value
667
651
5.43
<.0001
3.52
3.58
-8.15
<.0001
For the Access sample, significant differences were found with the population based on gender
such that the Access sample had a lower percentage of females compared to the population:
Table 3b.e. Access: Comparing Gender for Respondents and Non-Respondents
Gender by Respondent Type (%)
Female
Male
Survey
Respondents
NonRespondents
Total
7
93
11
89
11
89
Statistic
Chi-Square
DF
1
Value
502.54
Prob
<.0001
For the Access sample, significant differences were found with the population based on age
generation, such that a larger number of older Veterans and a fewer number of generation X
and YZ Veterans completed the survey:
13
Table 3c.e. Access: Comparing Age Generation for Respondents and Non-Respondents
Age Generation by Respondent Type (%)
Baby-Boomer
(ages 50-68)
Generation X
(ages 37-49)
Generation YZ
(ages 18-36)
Pre-Boomer
(ages 69+)
Survey
Respondents
NonRespondents
Total
49
27
32
14
22
20
10
42
35
27
9
13
Statistic
DF
Value
Prob
Chi-Square
3
17992
<.0001
For the Access sample, significant differences were found with the population based on race.
The differences indicate that survey respondents were less likely to be White or Black, and were
more likely to fall into Other category:
Table 3d.e. Access: Comparing Race for Respondents and Non-Respondents
Race by Respondent Type (%)
Asian
Black
White
Other
Survey
Respondents
NonRespondents
Total
2
10
46
42
4
17
62
18
4
15
59
22
Statistic
Chi-Square
DF
3
Value
7100
Prob
<.0001
For the Access survey, significant differences were found with the population based on
geographical region such that survey respondents were more from the Midwest and less from
the South:
Table 3e.e. Access: Comparing Census Region for Respondents and Non-Respondents
U.S. Census Region by Respondent Type (%)
Midwest
Northeast
South
West
Survey
Respondents
NonRespondents
Total
27
15
35
23
21
13
41
26
22
13
40
25
Statistic
Chi-Square
DF
4
Value
817
Prob
<.0001
14
For the Access sample, significant differences were found with the population based on branch
of service. The effects show that the survey respondents were slightly more likely to be in the
Navy and less likely to be in the Marines:
Table 3f.e. Access: Comparing Military Service Branch for Respondents and Non-Respondents
Military Service Branch by Respondent Type (%)
Air Force
Army
Marines
Navy
Other
Survey
Respondents
NonRespondents
Total
18
48
11
21
2
18
49
15
17
2
18
49
14
18
2
Statistic
Chi-Square
DF
4
Value
513
Prob
<.0001
For the Access survey, significant differences were found in war service era with less surveys
returned by Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) veterans
than by other war Veterans:
Table 3g.e. Access: Comparing War Participation in OIF and OEF for Respondents and NonRespondents
OIF and OEF War Service by Respondent Type (%)
Survey
Respondents
NonRespondents
Total
82
18
59
41
64
36
All others
OEF/OIF
Statistic
Chi-Square
DF
1
Value
6110
Prob
<.0001
Note: OIF is Operation Iraqi Freedom and OEF is Operation Enduring Freedom.
For the Access sample, significant differences were found with the population based on Benefit
Award. The data shows that more surveys were completed by veterans who receive lesser
awards under $500 than those who received $1,501 or more:
Table 3h.e. Access: Comparing Benefit Award for Respondents and Non-Respondents
Benefit Award by Respondent Type (%)
Survey
NonRespondents Respondents
$500 or less
$501-$1000
$1001-$1500
$1501 or more
53
15
13
18
43
17
17
23
Total
Statistic
Chi-Square
DF
3
Value
Prob
1086
<.0001
45
17
16
22
15
For the Access sample, significant differences were found with the population based on
Disability Entitlement. The data shows that more surveys were completed by Vietnam and
Peacetime veterans and less were completed by Gulf War Veterans:
Table 3i.e. Access: Comparing Entitlement for Respondents and Non-Respondents
Disability Entitlement by Respondent Type (%)
Survey
NonRespondents Respondents
31
17
46
6
Gulf War
Peacetime
Vietnam Era
Other
Total
67
12
19
2
Statistic
Chi-Square
DF
3
Value
15347
Prob
<.0001
60
13
24
3
For the Access sample, significant differences were found with the population based on days of
active service, such that survey respondents were more likely to have served 1,000 or less days
and less likely to have served 1,001 to 4,000 days compared to the population:
Table 3j.e. Access: Comparing Days of Active Service for Respondents and Non-Respondents
Days of Active Service by Respondent Type (%)
Survey
Respondents
NonRespondents
Total
62
34
40
11
26
23
8
19
17
18
21
20
1000 days
or less
1001-2000
days
2001-4000
days
4001 days
or more
Statistic
Chi-Square
DF
3
Value
9400
Prob
<.0001
For the Access sample, a Chi-square test showed war period differences such that a larger
number of Vietnam Veterans and a fewer number of Gulf War Veterans completed the survey:
Table 3k.e. Access: Comparing War Period for Respondents and Non-Respondents
War Period by Respondent Type (%)
Survey
NonRespondents Respondents
Gulf War
Korean Conflict
Peacetime Era
Vietnam Era
World War I & II
31
5
17
46
2
67
1
12
19
1
Total
60
2
13
24
1
Statistic
DF
Value
Prob
Chi-Square
4
15390
<.0001
16
For Compensation Servicing, there were significant differences found between mail and online
survey respondents. Similar to Access, the results show that satisfaction was higher for mail
respondents whereas advocacy was higher for the online respondents:
Table 3a.s. Servicing: T-Test Analysis of Mail vs. Online Survey Results
Rating Measure
Overall Satisfaction Index (100 - 1000
range)
Likelihood to inform others about VA
benefits (rating 1 - 4)
Mail
Online
t-statistic
p-value
636
612
5.44
<.001
3.48
3.54
-4.32
<.001
For the Servicing sample, significant differences were found with gender such that the Servicing
sample had a lower percentage of females compared to nonrespondents:
Table 3b.s. Servicing: Comparing Gender for Respondents and Non-Respondents
Gender by Respondent Type (%)
Female
Male
Survey
Respondents
NonRespondents
Total
6
94
10
90
9
91
Statistic
Chi-Square
DF
1
Value
140
Prob
<.0001
For the Servicing sample, significant differences were found with the population based on age
generation, such that a larger number of older Veterans and a fewer number of generation X
and YZ Veterans completed the survey:
Table 3c.s. Servicing: Comparing Age Generation for Respondents and Non-Respondents
Age Generation by Respondent Type (%)
Baby-Boomer
(ages 50-68)
Generation X
(ages 37-49)
Generation YZ
(ages 18-36)
Pre-Boomer
(ages 69+)
Survey
Respondents
NonRespondents
Total
57
44
47
9
20
17
5
17
14
29
19
21
Statistic
DF
Value
Prob
Chi-Square
3
2834
<.0001
For the Servicing sample, significant differences were found with the population based on race.
The differences indicate that survey respondents were less likely to be White or Black, and
more likely to fall into Other category:
17
Table 3d.s. Servicing: Comparing Race for Respondents and Non-Respondents
Race by Respondent Type (%)
Asian
Black
Other
White
Survey
Respondents
NonRespondents
Total
3
11
36
50
4
15
23
58
4
14
26
56
Statistic
Chi-Square
DF
3
Value
681
Prob
<.0001
For the Servicing survey, significant differences were found with the population based on
geographical region such that survey respondents were more from the Midwest and West and
less from the South:
Table 3e.s. Servicing: Comparing Census Region for Respondents and Non-Respondents
U.S. Census Region by Respondent Type (%)
Midwest
Northeast
South
West
Survey
Respondents
NonRespondents
Total
22
18
33
28
20
18
36
26
21
18
35
26
Statistic
Chi-Square
DF
3
Value
69
Prob
<.0001
For the Servicing sample, significant differences were found with the population based on
branch of service. The effects show that the survey respondents were slightly more likely to be
in the Navy and less likely to be in the Marines:
Table 3f.s. Servicing: Comparing Military Service Branch for Respondents and Non-Respondents
Military Service Branch by Respondent Type (%)
Air Force
Army
Marines
Navy
Other
Survey
Respondents
NonRespondents
Total
18
53
11
17
1
15
55
13
15
1
16
54
13
16
1
Statistic
Chi-Square
DF
4
Value
93
Prob
<.0001
For the Servicing survey, significant differences were found in war service era with less surveys
returned by OEF/OIF veterans than by other war Veterans:
18
Table 3g.s. Servicing: Comparing War Participation in OIF and OEF for Respondents and NonRespondents
OIF and OEF War Service by Respondent Type (%)
Survey
Respondents
NonRespondents
Total
88
12
75
25
79
21
All others
OEF/OIF
Statistic
Chi-Square
DF
1
Value
1136
Prob
<.0001
Note: OIF is Operation Iraqi Freedom and OEF is Operation Enduring Freedom.
For the Servicing sample, significant differences were found with the population based on
Benefit Award. Fewer surveys were completed by veterans who receive awards under $500
than those who received $1,001 or more:
Table 3h.s. Servicing: Comparing Benefit Award for Respondents and Non-Respondents
Benefit Award by Respondent Type (%)
Survey
NonRespondent Respondents
s
$500 or less
$501-$1,000
$1,001-$1,500
$1,501 or more
20
18
20
42
Total
22
18
19
41
Statistic
Chi-Square
DF
3
Value
Prob
30
<.0001
21
18
19
42
For the Servicing sample, significant differences were found with the population based on
Disability Entitlement. The data shows that more surveys were completed by Vietnam and
Peacetime veterans and less were completed by Gulf War Veterans:
Table 3i.s. Servicing: Comparing Entitlement for Respondents and Non-Respondents
Disability Entitlement by Respondent Type (%)
Survey
NonRespondents Respondents
Gulf War
Other
Peacetime
Vietnam Era
28
5
15
52
47
5
14
34
Total
Statistic
Chi-Square
DF
3
Value
1938
Prob
<.0001
42
5
15
38
For the Servicing sample, significant differences were found with the population based on days
of active service, such that survey respondents were more likely to have served 1,000 or less
days and less likely to have served 1,001 to 4,000 days compared to the population:
19
Table 3j.s. Servicing: Comparing Days of Active Service for Respondents and Non-Respondents
Days of Active Service by Respondent Type (%)
Survey
Respondents
NonRespondents
Total
63
50
54
8
17
15
7
12
11
23
20
21
1000 days
or less
1001-2000
days
2001-4000
days
4001 days
or more
Statistic
Chi-Square
DF
3
Value
1307
Prob
<.0001
For the Servicing sample, a Chi-square test showed war period differences such that a larger
number of Vietnam Veterans completed the survey and fewer numbers of Gulf War Veterans
completed the survey:
Table 3k.s. Servicing: Comparing War Period for Respondents and Non-Respondents
War Period by Respondent Type (%)
Survey
NonRespondents Respondents
Gulf War
Korean Conflict
Peacetime Era
Vietnam Era
World War I & II
28
3
15
52
2
47
3
14
34
2
Total
42
3
15
38
2
Statistic
DF
Value
Prob
Chi-Square
4
1959
<.0001
3.1 Survey Yield
In accordance with OMB “Standards and Guidelines for Statistical Surveys,” an agency must
appropriately measure, adjust for, report, and analyze unit and item non-response, when the
intended response for a targeted population is not met.1 In assessing Compensation’s data in
accordance with Section 3.2, and Guidelines 3.2.1-3.2.3, the unweighted unit response rate was
calculated as the ratio of the number of completed cases to the number of in-scope sample
cases (Ellis, 2000; AAPOR, 2000).
Table 3.1a.e below shows the sample distribution and response rate for the Compensation
Access target population:
1
As defined by OMB and FCSM, unit non-response occurs when a respondent fails to respond to all required response items
(i.e., fails to fill out or return a data collection instrument); item non-response occurs when a respondent fails to respond to one
or more relevant item(s) on a survey
20
Table 3.1a.e. Sample Distribution and Response Rates for Compensation Access Population
Total Compensation Access Population FY2015
Total records received
Duplicate records in sample file
Duplicate record history
Invalid Address
Invalid Values
Blanks
Do Not Contact
2
Total records available after cleaning
Total records selected
Undeliverable addresses
Total mailed (excludes undeliverable)
Total completed mail surveys
Total completed online surveys
Total completed surveys
3
Total completed surveys with Overall Index Score
4
Total Sample Response Rate
5
Eligible Sample Response Rate
315,883
3,754
3,743
15,146
20,219
0
2,035
270,986
160,000
6,531
153,469
28,150
8,455
36,605
35,138
21.96%
23.85%
2
Glossary of sample cleaning rules included in Appendix E.
Findings in the report are based on the Total Completed Surveys with Overall Index Score (N=35,138).
4
Response rate calculation per OMB Standards and Guidelines for Statistical Surveys, Section 3.2, Guideline 3.2.9
(includes undeliverables as number of non-contacted sample units known to be eligible).
5
Response rate calculation per Council of American Survey Research Organizations (CASRO) (includes number of
completed interviews with reporting units/number of eligible reporting units in sample). The American Association
for Public Opinion Research (APPOR) also uses this method for calculation and cites CASRO (APPOR Standard
Definitions, 2008, pp. 34).
3
21
Table 3.1a.s below shows the sample distribution and response rate for Compensation Servicing
target population:
Table 3.1a.s. Sample Distribution and Response Rates for Compensation Servicing Population
Total Compensation Servicing Population FY2015
Total records received
Duplicate records in sample file
Duplicate record history
Invalid address
Invalid values
Blanks
Do not contact
6
Total records available after cleaning
Total records selected
Undeliverable addresses
Total mailed (excludes undeliverable)
Total completed mail surveys
Total completed online surveys
Total completed surveys
7
Total completed surveys with Overall Index Score
8
Total Sample Response Rate
9
Eligible Sample Response Rate
449,568
7,479
34,557
14,586
11,405
0
552
380,989
60,000
1,833
58,167
11,962
4,068
16,030
15,015
25.03%
27.56%
Of the 315,883 total records received from Access, 44,897 records were purged from the
sample due to cleaning rules such as duplicate records, invalid addresses and values, blanks,
and do not contact opt outs. From the 44,897records purged, 3,743 records were purged due to
duplicate records across VBA’s other business line surveys (i.e. duplicate record history). In
Servicing we received a total of 315,883 records but we purged 68,579 records from the sample
due to cleaning rules such as duplicate records, invalid addresses and values, blanks, and do not
contact opt outs. Also, from the 68,579 records that were purged, there were 34,557 records
that were cleaned due to duplicate records across other business lines.
6
Glossary of sample cleaning rules included in Appendix E.
Findings in the report are based on the Total Completed Surveys with Overall Index Score (N=15,015).
8
Response rate calculation per OMB Standards and Guidelines for Statistical Surveys, Section 3.2, Guideline 3.2.9
(includes undeliverables as number of noncontacted sample units known to be eligible).
9
Response rate calculation per Council of American Survey Research Organizations (CASRO) (includes number of
completed interviews with reporting units/number of eligible reporting units in sample). The American Association
for Public Opinion Research (APPOR) also uses this method for calculation and cites CASRO (APPOR Standard
Definitions, 2008, pp. 34).
7
22
The purpose of the cleaning rules is to prevent respondents from being re-contacted if they
were previously selected to participate in any of VBA’s business line surveys in the past 12
months. The cleaning rule is a JDP and survey research best practice and is intended to promote
proper conduct in market research. About 14% of the total records provided for Access and
about 15% of the total records provided for Servicing were removed from the sample due to
these cleaning rules. It is unlikely that the cleaning rules impacted the unit non-response and
we were able to secure the designated number of records for both Servicing and Access.
Table 3.1b.e. Access: Weight/Person for Completed Surveys per Population
Completed Surveys
36,605
Access 2015 Population
315,883
Weight/Person
9
In Table 3.1b.e, the 9 in the Weight/Person column means that every survey
completed/returned represents the views of 9 Veterans using Compensation Access-benefits.
This was calculated by dividing the number of completed surveys into the population number.
Table 3.1b.s. Servicing: Weight/Person for Completed Surveys per Population
Completed Surveys
16,030
Servicing 2015 Population
449,568
Weight/Person
28
In Table 3.1b.s, the 28 in the Weight/Person column means that every survey completed and
returned represents the views of 28 Veterans using Compensation Servicing-benefits. This was
calculated by dividing the number of completed surveys into the population number.
To confirm the sample’s representativeness for both Access and Servicing, a comparison was
conducted among the total records provided and the records available after cleaning. The
intent of this analysis was to determine whether the cleaning rules caused the remaining
sample to vary in a meaningful way from the original sampling frame.
Table 3.1c.e (Access) and Table 3.1c.s (Servicing) indicate characteristics such as Gender, Age,
and Geographical Region are similar among the total records provided and the records available
after cleaning. Comparisons by state yield differences that are mostly less than 1% point, with a
few exceptions in Access where differences were wider for certain age ranges. Overall, these
comparisons suggest the cleaning rules did not significantly alter the proportion of respondent
characteristics provided in the original sampling frame.
23
Table 3.1c. Access: Comparing Gender, Generation, and U.S. States to Total Population
Gender
Female
Male
Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
U.S. State
AK
AL
AR
AZ
CA
CO
CT
DC
DE
FL
GA
HI
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
Total
Population
(%)
Records Available
(%)
% Point
Difference
10.66
89.34
11.1
88.9
0.44
-0.44
31.68
19.64
33.59
15.09
30.88
21.04
35.76
12.32
-0.8
1.4
2.17
-2.77
0.47
1.82
0.85
1.81
10.31
2.43
0.63
0.11
0.26
6.60
4.66
0.72
0.86
0.57
2.04
2.10
0.87
1.22
1.48
1.51
1.82
0.39
2.31
2.03
2.24
1.00
0.29
4.39
0.23
0.80
0.38
1.13
0.69
1.19
2.79
2.96
0.5
1.84
0.86
1.86
10.39
2.5
0.63
0.11
0.26
6.7
4.61
0.72
0.86
0.59
2.01
2.01
0.87
1.21
1.47
1.44
1.86
0.41
2.13
1.86
2.22
1.03
0.3
4.42
0.24
0.78
0.38
1.08
0.72
1.25
2.76
2.91
0.03
0.02
0.01
0.05
0.09
0.07
-0.01
0
0
0.1
-0.05
-0.01
0
0.03
-0.03
-0.09
0
-0.01
0
-0.07
0.03
0.01
-0.17
-0.17
-0.02
0.03
0.02
0.03
0.01
-0.02
-0.01
-0.06
0.02
0.06
-0.03
-0.06
24
Table 3.1c. Access: Comparing Gender, Generation, and U.S. States to Total Population (Continued)
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
Population
(%)
Records Available
(%)
% Point
Difference
2.37
1.61
2.76
0.27
2.69
0.30
2.87
10.40
0.69
4.01
0.13
3.00
1.22
0.67
0.28
2.34
1.61
2.68
0.27
2.65
0.32
2.87
10.62
0.7
4.07
0.13
3.05
1.21
0.69
0.3
-0.03
0
-0.07
0
-0.04
0.01
0
0.21
0.02
0.06
0
0.05
-0.01
0.02
0.02
Table 3.1c.s. Servicing: Comparing Gender, Generation, and U.S. States to Total Population
Gender
Female
Male
Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
U.S. State
AK
AL
AR
AZ
CA
CO
CT
DC
DE
FL
GA
HI
Total
Population
(%)
Records Available
(%)
% Point
Difference
10.15
89.85
9.41
90.59
-0.74
0.74
47.65
16.89
13.86
21.61
48.15
16.6
13.35
21.91
0.5
-0.29
-0.51
0.3
0.35
2.09
1.03
2.04
8.87
1.94
0.57
0.09
0.26
6.98
4.33
0.65
0.35
1.95
1.02
2.01
9.06
1.94
0.53
0.08
0.26
7.29
4.29
0.66
0
-0.14
-0.01
-0.03
0.19
0
-0.04
-0.01
0
0.31
-0.04
0
25
Table 3.1c.s Servicing: Comparing Gender, Generation, and U.S. States to Total Population (Continued)
IA
ID
IL
IN
KS
KY
LA
MA
MD
ME
MI
MN
MO
MS
MT
NC
ND
NE
NH
NJ
NM
NV
NY
OH
OK
OR
PA
RI
SC
SD
TN
TX
UT
VA
VT
WA
WI
WV
WY
Total
Population
(%)
Records Available
(%)
% Point
Difference
1.09
0.71
2.22
1.72
0.96
1.47
1.7
1.53
1.24
0.55
2.76
2.09
2.63
1.18
0.47
4.69
0.34
0.89
0.44
1.4
0.94
1.06
3.05
3.01
2.6
1.61
2.73
0.31
2.76
0.44
3.02
8.97
0.72
2.99
0.2
2.51
1.35
1.11
0.25
1.08
0.71
2.21
1.64
0.96
1.46
1.64
1.52
1.16
0.56
2.7
2.07
2.64
1.15
0.49
4.94
0.35
0.92
0.43
1.34
0.92
1.03
2.99
3
2.6
1.59
2.65
0.31
2.69
0.46
3.04
9.26
0.71
3.02
0.2
2.61
1.28
1.12
0.25
-0.01
0
-0.01
-0.08
0
-0.01
-0.05
0
-0.08
0.01
-0.06
-0.02
0.01
-0.03
0.01
0.25
0.01
0.03
-0.01
-0.06
-0.02
-0.02
-0.06
-0.01
-0.01
-0.02
-0.08
-0.01
-0.07
0.02
0.02
0.29
-0.01
0.02
0
0.1
-0.07
0.01
0
26
3.2 Missing Data Patterns and Mechanisms
In accordance with the OMB “Standards and Guidelines for Statistical Surveys” Guidelines 3.2.9
and 3.2.11, an investigation of missing data patterns was conducted on the 36,605 total surveys
received for Access and 16,030 total surveys received for Servicing. In order to assess the
distribution of missing data, a procedure was performed to process missing values involving
iterative multiple imputation chains using expectation–maximization (MCMC) algorithms and
divide these into distribution interval groupings, Pierchala, Carl E. (2001). This was done on the
key measures of the Overall Satisfaction Index (see Appendix A for calculation) and Advocacy
ratings related to Veterans’ likelihood to recommend VA benefits.
As shown in Tables 3.2.e and 3.2.s for Access and Servicing respectively, there were no
indications of unusual patterns for missing data. For more discussion of missing data
mechanisms (MCAR, MAR, and MNAR), please see Appendix A.
Table 3.2.e. Access: Missing Data Patterns in Satisfaction and Advocacy (0 = missing, 1 = data)
Group Means
Group
1
2
3
4
Overall
Satisfaction
Likelihood
to inform
others
Freq
Percent
OSAT
Index
Age
% Male
0
0
1
1
0
1
0
1
298
843
425
30764
1%
3%
1%
95%
656
667
654
663
62
67
64
60
91%
95%
94%
93%
Table 3.2.s. Servicing: Missing Data Patterns in Satisfaction and Advocacy (0 = missing, 1 = data)
Group Means
Group
Overall
Satisfaction
Likelihood
to inform
others
Freq
Percent
OSAT
Index
Age
% Male
0
0
1
1
0
1
0
1
37
322
251
14402
0%
2%
2%
96%
587
627
612
630
76
69
66
63
91%
95%
90%
94%
0
0
1
1
27
3.3 Margin of Error
The margin of error expresses the maximum expected difference between the true population
parameter and a sample estimate of that parameter. It is often used to indicate the accuracy of
survey results. The larger the margin of error around an estimated value, the less accurate the
estimated value will be. Larger samples are more likely to yield results close to the true
population quantity and thus have smaller margins of error than smaller samples.
Based on a sample of 153,469 Veterans, the Overall Satisfaction Index for the Access study is
662 and has a margin of error of 2 index points, on a 1,000 point scale, at the 95% confidence
level. This indicates that if the survey were repeated many times with different samples, the
true mean Overall Satisfaction Index would fall within 2 index points 95% of the time.
Table 3.3.e below demonstrates relative decreases in margin of error as the study sample size
increases. A 30% response rate (46,041 completes) would be associated with a margin of error
of 2 index points, similar to the margin of error for a 40% response rate (61,388 completes).
Results from this analysis indicate the Overall Satisfaction Index (OSAT) calculated from the
Access study is an accurate measurement of the true population mean.
Table 3.3.e. Access: Margin of Error for Larger Sample Sizes
Sample
Response
Rate
Completes
(N)
OSAT
(mean)
Standard
Deviation
Standard
Error
Margin of error
(95% confidence
interval)
153,469
153,469
153,469
153,469
153,469
153,469
153,469
23.85%
20%
30%
40%
50%
60%
80%
36,605
30,694
46,041
61,388
76,735
92,081
122,775
662
662
662
662
662
662
662
213
213
213
213
213
213
213
1.1
1.2
1.0
0.9
0.8
0.7
0.6
2
2
2
2
2
1
1
Based on a sample of 58,167 Veterans, the FY15 Overall Satisfaction Index for the Servicing
study is 630 and has a margin of error of 3 index points, on a 1,000 point scale, at the 95%
confidence level. This indicates that if the survey were repeated many times with different
samples, the true mean Overall Satisfaction Index would fall within 3 index points 95% of the
time.
Table 3.3.s below demonstrates relative decreases in margin of error as the study sample size
increases. A 30% response rate (17,450 completes) would be associated with a margin of error
of 3 index points, similar to the margin of error for a 40% response rate (23,267 completes).
Results from this analysis indicate the Overall Satisfaction Index (OSAT) calculated from the
Servicing study is an accurate measurement of the true population mean, which is reported on
a 1,000 point scale.
28
Table 3.3.s. Servicing: Margin of Error for Larger Sample Sizes
Sample
Response
Rate
Completes
(N)
OSAT
(mean)
Standard
Deviation
Standard
Error
Margin of error
(95% confidence
interval)
58,167
58,167
58,167
58,167
58,167
58,167
58,167
27.56%
20%
30%
40%
50%
60%
80%
16,030
11,633
17,450
23,267
29,084
34,900
46,534
630
630
630
630
630
630
630
222
222
222
222
222
222
222
1.8
2.1
1.7
1.5
1.3
1.2
1.0
3
4
3
3
3
2
2
In the margin of error analysis noted on the previous page and in subsequent analyses included
in this report, the Overall Satisfaction Index Score is the main dependent variable and is the
basis for the analysis. The Overall Satisfaction Index score is the survey metric that VBA utilizes
to measure customer satisfaction and benchmark performance against other industries. It is the
primary measurement in all reports. The Overall Satisfaction Index encompasses all aspects of
the customer experience10, and can therefore be used as a reliable indicator for the presence or
absence of respondent bias in the survey results as a whole. For these reasons, the Overall
Satisfaction Index score is used as the main dependent variable in the margin of error analysis
and subsequent t-test analyses included in this report.
3.3.1 Sampling Distribution
Respondent characteristics such as gender and age were compared to that of the total sample
to determine whether respondents and non-respondents differed on key variables of interest.
Compared to the population of all eligible respondents (Access 160,000, Servicing 60,000),
survey respondents demonstrate the same gender characteristics. For Access, Table 3.3.1.e
below illustrates 7% of survey respondents were female and 93% were male, similar to the total
sample population. The distribution of age shows that survey respondents tend to be older.
10
Explanation of J.D. Power Index Model Calculation included in Methodology.
29
Table 3.3.1.e. Access: Comparing Gender and Age of Survey Respondents to Total Sample
Gender
Female
Male
Age Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
Respondents
(%)
Sample
Size (N)
Total
Sample (%)
Sample
Size (N)
% Point
Difference
7
93
2209
29662
11
89
16364
138938
4
-4
48
14
10
28
16286
4608
3341
9420
32
20
35
13
50676
31938
56152
21234
-17
6
25
-15
For Servicing, Table 3.3.1.s below illustrates 6% of survey respondents were female and 94%
were male, similar to the total sample population. The distribution of age shows that survey
respondents tend to be older.
Table 3.3.1.s. Servicing: Comparing Gender and Age of Survey Respondents to the Total Sample
Gender
Female
Male
Age Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
Respondents
(%)
Sample
Size (N)
Total
Sample (%)
Sample
Size (N)
% Point
Difference
6
94
973
14474
9
91
5048
53220
2
-2
56
9
5
30
8959
1447
747
4874
47
17
14
22
28384
10169
8276
13171
-9
8
9
-8
3.3.2 Distribution of Overall Satisfaction Index Scores
Following the comparison of sampling distributions, a comparison of Overall Satisfaction Index
scores was conducted to determine whether differences in age and gender among respondents
correlate with differences in overall satisfaction.
For Access, Table 3.3.2.e below indicates differences in Overall Satisfaction Index scores are
notable between gender groups. On average, females tend to rate their experience 14 index
points lower than males (648 vs. 662). Comparing age groups reveals that Pre-Boomer had the
highest overall satisfaction with Generation YZ much lower.
30
Table 3.3.2.e. Access: Overall Satisfaction Scores for Gender and Age Groups
Characteristics
Gender
Female
Male
Age Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
OSAT (mean)
Standard Deviation
Sample Size (N)
648
662
215
214
2164
28469
658
642
634
692
214
224
218
202
15803
4544
3281
8702
For Servicing, Table 3.3.2.s below indicates differences in Overall Satisfaction Index scores are
notable between gender groups. On average, females tend to rate their experience 5 index
points higher than males (633 vs. 628). Comparing age groups reveals that Pre-Boomer had the
highest overall satisfaction with Generation XYZ much lower.
Table 3.3.2.s. Servicing: Overall Satisfaction Scores for Gender and Age Groups
Characteristics
Gender
Female
Male
Age Generation
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
OSAT (mean)
Standard Deviation
Sample Size (N)
633
628
225
223
914
13569
624
596
593
658
223
229
225
215
8530
1405
726
4351
3.3.3 Analysis for Demographic Differences
T-test analyses were conducted to determine whether differences in demographic groups
produced statistical differences in Overall Satisfaction (OSAT) scores. T-tests are typically used
to determine whether or not the difference between two groups’ averages most likely reflect a
meaningful difference in the population from which the groups were sampled.
For Access, both gender and war participation differences were significantly different such that
males and non-OEF/OIF veterans had higher levels of overall satisfaction:
31
Table 3.3.3a.e. Access: T-Test Analysis for Pairs of Characteristics in Veterans’ Satisfaction
Characteristics
Gender
Female vs. Male
War Participation
OEF/OIF vs. All Others
T-Test Statistic
Statistical Difference (95%
confidence level)
-2.95
Yes
7.22
Yes
For Servicing, the differences for gender and war participation were both statistically
significant:
Table 3.3.3a.s. Servicing: T-Test Analysis for Pairs of Characteristics in Veterans’ Satisfaction
Characteristics
Gender
Female vs. Male
War Participation
OEF/OIF vs. All Others
T-Test Statistic
Statistical Difference (95%
confidence level)
0.66
No
1.97
Yes
Analyses of Variance (ANOVA) were conducted to determine whether differences in
demographic groups produced statistical differences in Overall Satisfaction scores. This
analysis is typically used to determine whether or not the difference among the average of
three or more groups most likely reflects a meaningful difference in the population from which
the groups were sampled.
For Access, differences in Overall Satisfaction by generation were significant (F = 92.30, p-value
< .0001) such that older survey respondents had higher levels of satisfaction:
Table 3.3.3b.e. Access: Overall Satisfaction for Generation
Generation
OSAT (mean)
Sample Size (N)
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
658
642
634
692
15803
4544
3281
8702
For Access, differences in Overall Satisfaction by region were significant (F = 89.03, p-value <
.0001) such that the Midwest respondents had the highest levels of satisfaction:
32
Table 3.3.3c.e. Access: Overall Satisfaction for Regions
Regions
OSAT (mean)
Sample Size (N)
Midwest
Northeast
South
West
688
680
644
651
8556
4776
11243
7498
For Access, racial differences in Overall Satisfaction were not significant (F = 100.56, p-value <
.0001):
Table 3.3.3d.e. Access: Overall Satisfaction for Race
Race
OSAT (mean)
Sample Size (N)
Asian
Black
Other
White
684
638
683
635
587
2405
10370
11207
For Access, differences in Overall Satisfaction by branch of service were significant (F = 5.95, pvalue < .0001) such that respondents from the Army had the highest levels of satisfaction:
Table 3.3.3e.e. Access: Overall Satisfaction for Military Service Branches
Military Service
Branches
OSAT (mean)
Sample Size (N)
Air Force
Army
Marines
Navy
Other
659
667
659
662
629
5914
15378
3633
6798
607
For Access, differences in Overall Satisfaction by Benefit Award were significant (F = 283.72, pvalue < .0001) such that respondents receiving the highest awards had the highest levels of
satisfaction:
Table 3.3.3f.e. Access: Overall Satisfaction for Benefit Award
Benefit Award
OSAT (mean)
Sample Size (N)
$500 or less
$501-$1000
$1001-$1500
$1501 or more
635
665
691
722
17252
4882
4289
5904
33
For Access, differences in Overall Satisfaction by Entitlement were significant (F = 106.26, pvalue < .0001) such that respondents in the Other category had the highest levels of
satisfaction:
Table 3.3.3g.e. Access: Overall Satisfaction for Entitlement
Entitlement
OSAT (mean)
Sample Size (N)
Gulf War Disability
Other
Peacetime Disability
Vietnam Era Disability
638
718
656
674
9894
2018
5575
14843
For Access, differences in Overall Satisfaction by days of active service were significant (F =
81.17, p-value < .0001) such that respondents who had “1000 days or less” had the highest
levels of satisfaction:
Table 3.3.3h.e. Access: Overall Satisfaction for Days of Active Service
Days of Active
Service
1,000 days or less
1,001-2,000 days
2,001-4,000 days
4,001 days or more
OSAT (mean)
Sample Size (N)
677
638
629
645
20,148
3,637
2,717
5,828
For Access, differences in Overall Satisfaction by War Period were significant (F = 79.83, p-value
< .0001) such that respondents from the Korean and World War conflicts had the highest levels
of satisfaction:
Table 3.3.3i.e. Access: Overall Satisfaction for War Period
War Period
Gulf War
Korean Conflict
Peacetime Era
Vietnam Era
World War I & II
OSAT (mean)
Sample Size (N)
638
718
656
674
718
9896
1473
5575
14844
542
For Servicing, differences in Overall Satisfaction by generation were significant (F = 43.58, pvalue < .001) such that older respondents had the highest levels of satisfaction:
34
Table 3.3.3b.s. Servicing: Overall Satisfaction for Generation
Generation
OSAT (mean)
Sample Size (N)
Baby Boomer
Generation X
Generation YZ
Pre-Boomer
624
596
593
658
8530
1405
726
4351
For Servicing, differences in Overall Satisfaction by region were significant (F = 51.26, p-value <
.0001) such that respondents from the Northeast had the highest levels of satisfaction:
Table 3.3.3c.s. Servicing: Overall Satisfaction for Regions
Regions
OSAT (mean)
Sample Size (N)
Midwest
Northeast
South
West
639
673
614
612
3259
2593
4788
4040
For Servicing, racial differences in Overall Satisfaction were significant (F = 28.23, p-value < .001)
such that Asian respondents had the highest levels:
Table 3.3.3d.s. Servicing: Overall Satisfaction for Race
Race
OSAT (mean)
Sample Size (N)
Asian
Black
Other
White
641
595
650
609
306
1095
3444
4791
For Servicing, differences in Overall Satisfaction by branch of service were not significant (F =
0.63, p-value = 0.6398):
Table 3.3.3e.s. Servicing: Overall Satisfaction for Military Service Branches
Military Service
OSAT (mean)
Sample Size (N)
Air Force
Army
Marines
Navy
Other
628
631
627
631
610
2629
7944
1698
2529
212
35
For Servicing, differences in Overall Satisfaction by Benefit Award were significant (F = 207.51, pvalue < .0001) such that those respondents with the highest awards had the highest levels of
satisfaction:
Table 3.3.3f.s. Servicing: Overall Satisfaction for Benefit Award
Benefit Award
OSAT (mean)
Sample Size (N)
$500 or less
$501-$1000
$1001-$1500
$1501 or more
574
589
618
679
2945
2761
2981
6325
For Servicing, differences in Overall Satisfaction by Entitlement were significant (F = 52.45, pvalue < .0001) such that respondents in the Other category had the highest levels:
Table 3.3.3g.s. Servicing: Overall Satisfaction for Entitlement
Entitlement
OSAT (mean)
Sample Size (N)
Gulf War Disability
Other
Peacetime Disability
Vietnam Era Disability
609
675
599
646
4169
813
2299
7731
For Servicing, differences in Overall Satisfaction by days of active service were significant (F =
37.38, p-value <.0001) such that respondents with “1000 days or less” had the highest levels:
Table 3.3.3h.s. Servicing: Overall Satisfaction for Days of Active Service
Days of Active
Service
1000 days or less
1001-2000 days
2001-4000 days
4001 days or more
OSAT (mean)
Sample Size (N)
641
582
592
626
9403
1197
1029
3383
For Servicing, differences in Overall Satisfaction by War Period were significant (F = 38.95, pvalue < .0001) such that respondents from the Korean and World War conflicts had the highest
levels:
36
Table 3.3.3i.s. Servicing: Overall Satisfaction for War Period
War Period
OSAT (mean)
Sample Size (N)
609
668
599
646
684
4182
480
2303
7737
310
Gulf War
Korean Conflict
Peacetime Era
Vietnam Era
World War I & II
3.3.4 Data Imputation Analysis for Demographic Differences
A pairwise comparison t-test analysis was done to evaluate whether data imputation for
missing values across significant demographic differences shown in section 3.3.3 would impact
Overall Satisfaction Index Scores. This analysis included survey raking across demographic
differences as one level of comparison.
These results (Tables 3.3.4a.e and 3.3.4a.s) show that there were no significant differences
between the non-imputed mean and the imputed mean of the satisfaction index across
demographics, sample sizes, nor survey raked values. We want to highlight that after statistical
adjustment for the differences found between respondents and non-respondents reported
earlier, there were no differences in overall satisfaction levels. These results support the
conclusion that the survey’s findings for Veterans’ overall satisfaction ratings are accurate.
Table 3.3.4a.e. Access: Comparison of Imputed vs. Non-Imputed on Veterans’ Satisfaction
T-Test Analysis on Imputed vs. Non-Imputed raked for Demographic Differences
Overall Satisfaction Index
(100 - 1000 range)
Imputed demographics
(32,330 final sample size)
Imputed survey-raked demographics
(32,330 final sample size)
Imputed survey-raked demographics
(33,655 total respondents)
mean
(imputed)
mean (nonimputed)
t-statistic
p-value
662.70
662.65
-0.03
0.97
653.46
653.60
0.08
0.94
654.23
653.32
-0.54
0.59
Note: Non-imputed is based on the 32,330 final cleaned sample size used in this report.
37
Table 3.3.4a.s. Servicing: Comparison of Imputed vs. Non-Imputed on Veterans’ Satisfaction
T-Test Analysis on Imputed vs. Non-Imputed raked for Demographic Differences
Overall Satisfaction Index
(100 - 1000 range)
Imputed demographics
(15,012 final sample size)
Imputed survey-raked demographics
(15,012 final sample size)
Imputed survey-raked demographics
(16,027 total respondents)
mean
(imputed)
mean (nonimputed)
t-statistic
p-value
630.52
629.77
-0.29
0.77
622.34
621.65
-0.27
0.79
623.30
621.19
-0.83
0.40
Note: Non-imputed is based on the 15,012 final cleaned sample size used in this report.
Survey Raking for Sample Weights to Adjust for Differences and Compare Overall Satisfaction
and Advocacy Ratings
The procedure known as “raking” adjusts a set of data so that its marginal totals match
specified control totals on a specified set of variables. The term suggests an analogy with the
process of smoothing the soil in a garden plot by alternately working it back and forth with a
rake in two perpendicular directions (Izrael and Battaglia (2004)).
Survey raking is an iterative sample-balancing algorithm-based technique that provides sample
weighting convergence across multiple variables and multiple categories (Battaglia, Izrael,
Hoaglin, and Frankel (2009)).
In keeping with OMB “Standards and Guidelines for Statistical Surveys” Guidelines 3.2.12 and
3.2.13, JDP selected the best statistical method to simultaneously adjust for multiple
differences between groups by applying a survey raking procedure, see Anderson, L., and R.D.
Fricker, Jr. (2015).
The JDP raking procedure is a proprietary improved version based on the excellent methods
initially developed by Izrael and Battaglia (2000, 2004) and Battaglia, Izrael, Hoaglin, and
Frankel (2004). JDP raking improvements are primarily related to better handling of low cell
values during iterative convergence processing. For this analysis, 50 iterations were set
(although fewer were needed) to converge on the best sample weights (.2 estimation margin)
to simultaneously adjust for non-response bias in age, race, region, and war (service era)
demographic categories. For additional background about survey raking methodologies, see
Wallace and Rust (1996).
The estimated population distributions are used as convergence targets. In this case, the
dataset of all eligible respondents for Access (160,000) and Servicing (60,000) was used as the
estimated population to derive sample weightings for the Access survey respondents (36,605)
and the Servicing survey respondents (16,030).
38
In accordance with OMB “Standards and Guidelines for Statistical Surveys” Guideline 3.2.13, a
series of t-tests were conducted to determine whether non-response bias in demographic areas
produced statistical differences in Overall Satisfaction Index scores and Advocacy ratings.
Typically, t-tests are used to determine whether differences between the averages and
variances of two groups reflect a meaningful difference in the population. The sample
weightings derived from the survey raking procedure were included in the t-tests to equalize
the survey respondent differences with non-respondents.
For Access, there were significant differences in Overall Satisfaction Index scores and Advocacy
when the data was adjusted for demographic differences between survey respondents and
non-respondents. However, the actual differences in ratings are small (663 vs 654 for OSAT,
and 3.53 and 3.55 for Advocacy). The effect size for Overall Satisfaction as measured by
Cohen’s D = .04 is considered less than a “small” effect (Cohen’s D = 0.20). Likewise, the effect
size for advocacy was also very small (Cohen’s D = -0.03). This suggests that the statistical
significance was magnified by the large sample numbers. In conclusion, we would point to the
findings reported in Table 3.3.4a.e, where the overall results support the conclusion that the
survey’s findings for Veterans’ overall satisfaction ratings are accurate.
Table 3.3.4b.e. Access: Overall Satisfaction and Advocacy for Survey Respondents Unweighted
and Weighted
Analysis of Survey Respondent Scores with Weighted Adjustment for Non-Response Bias
Standard
Standard
Rating
Mean
Mean
tpDeviation
Deviation
Measure
(Unweighted) (Weighted)
statistic value
(Unweighted)
(Weighted)
Overall
Satisfaction
Index (100 1000 range)
Likelihood to
inform others
about VA
benefits
(rating 1 - 4)
663
654
213
218
5.33
<.001
3.53
3.55
.62
.62
-3.59
<.001
For Servicing, there were significant differences in Overall Satisfaction but not advocacy when
the data was adjusted for demographic differences between survey respondents and nonrespondents. However, the actual differences in Satisfaction index are small (630 vs 622).
The effect size for Overall Satisfaction as measured by Cohen’s D = .04 is considered less than a
“small” effect (Cohen’s D = 0.20). This suggests that the statistical significance was magnified
by the large sample numbers. In conclusion, we would point to the findings reported in Table
3.3.4a.s, where the overall results support the conclusion that the survey’s findings for
Veterans’ overall satisfaction ratings are accurate.
39
Table 3.3.4b.s. Servicing: Overall Satisfaction and Advocacy for Survey Respondents
Unweighted and Weighted
Analysis of Survey Respondent Scores with Weighted Adjustment for Non-Response Bias
Standard
Standard
Rating
Mean
Mean
tpDeviation
Deviation
Measure
(Unweighted) (Weighted)
statistic value
(Unweighted)
(Weighted)
Overall
Satisfaction
Index (100 1000 range)
Likelihood to
inform others
about VA
benefits
(rating 1 - 4)
630
622
222
224
3.15
<.01
3.50
3.50
.66
.66
-.90
.37
Findings
Results from the non-response bias analysis indicate that the Overall Customer Satisfaction
Index score and the Advocacy ratings from the Compensation study reflects the experience of
all Veterans and beneficiaries who: 1) received a decision for their application for
compensation benefits with the past 30 days, 2) may include individuals who were found
eligible on a new or subsequent claim, 3) those who have been denied and are not appealing
the decision and 4) those who began receiving benefits six to eighteen months ago
Sample Cleaning: Initial comparisons on Age, Gender, and Geographical characteristics
between the total records provided and the records available after cleaning (see Survey Yield,
Section 3.1), suggests the sample utilized in the study exhibits similar characteristics as the total
sample. Additional comparisons (see Margin of Error and Sampling Distribution, Section 3.3,)
suggest the sample cleaning rules did not impact the sample’s representativeness and the
results are conclusive.
Non-Response Bias Analysis: Results from the non-response bias analysis did show group
differences for age, gender, region, race, benefit award, entitlement type, military branch, days
of service, and war participation between survey respondents and non-respondents. After
correcting for these differences using a recommended sample-balancing survey raking method
to derive sample weights (see Margin of Error, Section 3.3.4 Data Imputation Analysis for
Demographic Variables), no differences were found in the Overall Satisfaction Index scores and
Advocacy ratings (likelihood inform others about VA benefits). Some differences were found
between weighted and unweighted survey indices but the effects were shown to be small and
the statistical significance was due to the large sample numbers.
40
Item Response Rate Calculations: Results from the survey item response rate
calculations indicate high item response rates, with none falling below OMB guidelines (see
Appendix B for Item Response Rates). According to OMB Guideline 3.2.10, given that neither
study had a response rate lower than 70%, a non-response bias analysis was not necessary at
the item level.
The research and approach taken by JDP are in accordance with sound market research and
current best practices from the American Association for Public Opinion Research (AAPOR)
regarding response rate recommendations: “Results that show the least bias have turned out,
in some cases, to come from surveys with less than optimal response rates. Experimental
comparisons have also revealed few significant differences between estimates from surveys
with low response rates and short field periods and surveys with high response rates and long
field periods.” See AAPOR “Response Rates – An Overview” (2015) and Special Issue of Public
Opinion Quarterly "Nonresponse Bias in Household Surveys" (Singer, 2006).
Conclusion
The Overall Satisfaction Index score and Advocacy rating (likelihood to inform others about VA
benefits) are not impacted in any meaningful way by non-response bias. This analysis confirms
that the data collected during Fiscal Year 2015 is valid.
The FY15 Voice of the Veteran Line of Business Tracking Satisfaction Study data for the
Compensation Access and Servicing surveys can be used to infer reliable overall customer
satisfaction scores and advocacy ratings. The overall customer satisfaction index score reflects
the experience of all Veterans and beneficiaries who: 1) received a decision for their application
for compensation benefits with the past 30 days, 2) may include individuals who were found
eligible on a new or subsequent claim, 3) those who have been denied and are not appealing
the decision and 4) those who began receiving benefits six to eighteen months ago.
The sample utilized in the study exhibits similar characteristics for age, gender, and
geographical characteristics as the total sample provided. This indicates the sample cleaning
rules did not impact the sample’s representativeness.
While the results from the non-response bias analysis did show group differences on most of
the demographic characteristics between survey respondents and non-respondents, there were
no differences found in Veterans’ overall satisfaction and advocacy (likelihood to inform others
about VA benefits). This was after correcting for these differences using a recommended
sample-balancing survey raking method to derive sample weights. Some differences were
found between weighted and unweighted survey indices but the effects were shown to be
small and the statistical significance was due to the large sample numbers. JDP conducted all
necessary statistical tests in accordance with OMB standards.
J.D. Power certifies the results contained within this report.
41
References
Anderson, L., and R.D. Fricker, Jr. (2015). Raking: An Important and Often Overlooked Survey Analysis
Tool, Phalanx, http://faculty.nps.edu/rdfricke/docs/Analysis%20process_v4.pdf
American Association for Public Opinion Research (2008). Standard Definitions: Final Disposition of
Case Codes and Outcome Rates for Surveys. Ann Arbor, Michigan: AAPOR.
(http://www.aapor.org/AAPORKentico/AAPOR_Main/media/MainSiteFiles/Standard_Definitions_07
_08_Final.pdf).
American Association for Public Opinion Research (2015). “Response Rates – An Overview”
http://www.aapor.org/AAPORKentico/Education-Resources/For-Researchers/Poll-SurveyFAQ/Response-Rates-An-Overview.aspx
Battaglia, Michael P., Izrael, David, Hoaglin, David C., and Frankel, Martin R. (2004), “To Rake or Not To
Rake Is Not the Question Anymore with the Enhanced Raking Macro.” Proceedings of the 29th Annual
SAS Users Group International Conference, Paper 207.
Battaglia, Michael P., Izrael, David, Hoaglin, David C., and Frankel, Martin R. (2009). Practical
Considerations in Raking Survey Data. Survey Practice, Vol 2, No. 5.
Baum, Herbert M., Ph.D.; Chandonnet, Anna M.A.; Fentress, Jack M.S., M.B.A.; and Rasinowich, Colleen,
B.A. (2012). “Mixed-Mode Methods for Conducting Survey Research”. Data Recognition
Corporation. http://www.datarecognitioncorp.com/survey-services/Documents/Mixed-ModeMethods-for-Conducting-Survey-Research.pdf
Dillman, D. A. and J.D. Power (2015), Conference call discussion on non-response bias, avoidance
methods, and post-hoc sample weighting between Dr. Dillman and JDP (Greg Truex, Jay Meyers,
Ph.D., Lee Quintanar, Ph.D.), May 20, 2015 (2pm PDT).
Dillman, D. A. (2014). Internet, Phone, Mail and Mixed-Mode Surveys: The Tailored Design Method.
Fourth Edition. John Wiley & Sons, Inc: New York.
Ellis, J. M. (2000). Estimating the Number of Eligible Respondents for a Telephone Survey of LowIncidence Households. Paper presented at the annual meeting of the American Association for Public
Opinion Research, Portland OR, May 21, 2000.
Federal Committee on Statistical Methodology’s Statistical Policy Working Paper 31, Measuring and
Reporting Sources of Error in Surveys (2001). Washington, D.C.
Izrael, David, Hoaglin, David C., and Battaglia, Michael P. (2000), “A SAS Macro for Balancing a Weighted
Sample.” Proceedings of the Twenty-Fifth Annual SAS Users Group International Conference, Paper
275.
Izrael, David, Hoaglin, David C., and Battaglia, Michael P. (2004), “Tips and Tricks for Raking Survey Data
(a.k.a. Sample Balancing).” Proceedings of the 2004 American Association for Public Opinion
Research (AAPOR) Conference.
42
Malhotra, N.K, and Birks, D.F. (2007). Marketing Research: An Applied Approach, 3rd edition. Prentice
Hall/Financial Times: England.
Pierchala, Carl E. (2001). PROC MI® as the Basis for a Macro for the Study of Patterns of Missing Data.
Northeast SAS Users Group. http://www.lexjansen.com/nesug/nesug03/st/st009.pdf
Singer, E. (2006). Special Issue: Nonresponse Bias in Household Surveys. Public Opinion Quarterly, Vol
70, Issue 5.
U.S. Office of Management and Budget (1990), "Survey Coverage", Statistical Policy Working Paper 17,
Washington, D.C.
U.S. Office of Management and Budget Publication (January 2006). “When Designing Surveys for
Information Collections”. The Office of Management and Budget, 725 17th Street, NW. Washington,
D.C. 20503 USA
U.S. Office of Management and Budget Publication (September 2006). “Standards and Guidelines for
Statistical Surveys”. The Office of Management and Budget, 725 17th Street, NW. Washington, D.C.
20503 USA
U.S. Office of Management and Budget Publication (2008). VBA Compensation OMB - Part B Supporting
statement for “Collections of Information Employing Statistical Methods”. Washington, D.C.
Vogt, W. Paul, Vogt, Elaine R., Gardner, Dianne C., and Haeffele, Lynne M. (2014). Selecting the Right
Analyses for Your Data - Quantitative, Qualitative, and Mixed Method. Guilford Press, New York, NY.
Wallace, Leslie and Rust, Keith (1996). A Comparison of Raking and Poststratification Using 1994 NAEP
Data. Leslie Wallace, West Inc., 584-589.
43
Appendix A
Missing Data Patterns and Mechanisms
An excellent discussion of missing data patterns, mechanisms, and research analysis methods is
provided in Vogt, W. Paul, Vogt, Elaine R., Gardner, Dianne C., and Haeffele, Lynne M. (2014).
An overview of the missing data types and issues is described below:
Understanding the reasons why data is missing can be useful in analyzing the remaining data.
If values are missing at random, the data sample may still be representative of the population;
however, if the values are missing systematically, analysis may be harder.
Missing completely at random. Values in a data set are missing completely at random
(MCAR) if the events that lead to any particular data-item being missing are independent
both of observable variables and of unobservable parameters of interest, and occur entirely
at random. When data are MCAR, the analyses performed on the data are unbiased;
however, data are rarely MCAR.
Missing at random. Missing at random (MAR) is an alternative, and occurs when related to
a particular variable, but is not related to the value of the variable that has missing data. An
example of this is accidentally omitting an answer on a questionnaire.
Missing not at random. Missing not at random (MNAR) is data that is missing for a specific
reason (i.e. the value of the variable that is missing is related to the reason it is missing). An
example of this is if a certain question on a questionnaire tends to be skipped deliberately
by participants with certain characteristics. Graphical models can be used to describe the
missing data mechanism in detail.
While it is clear that MNAR can introduce statistical bias, there is no definitive test, see Vogt et
al. (2014). It is also clear that MCAR is rarely evident in research data and most tests of it will
fail. However, MAR is fully acceptable for valid statistical analyses (Vogt et. al, 2014). MAR is
essentially “missing partially at random” whereby the intra-group missingness remains random
despite some differences between group tendencies. Graphical data representations are the
typical tool used in assessment as described above and in Pierchala, Carl E. (2001).
See Section 3.2 Missing Data Patterns and Mechanisms for findings specific to Compensation’s
data.
44
Appendix B
Item Response Rates
In accordance with OMB “Standards and Guidelines for Statistical Surveys,” Section 3.2,
Guidelines 3.2.6-3.2.7, the item response rate was calculated as the ratio of the number of
respondents for whom an in-scope response was obtained to the number of respondents who
were asked to answer that item. The number asked to answer an item is the number of unitlevel respondents minus the number of respondents with a valid skip pattern. In addition to
item response rate, total item response rate was calculated as the product of the overall unit
response rate and the item response rate for each item. The purpose of these calculations is to
assess the item non-response, which occurs when one or more survey items are left blank in an
otherwise completed questionnaire. Tables B1.e and B1.s display the item and total item
response rates for these surveys.
The OMB “Standards and Guidelines for Statistical Surveys” (guideline 3.2.10) states an item
non-response analysis should be conducted for items with an item response rate of less than
70%. Since none of the survey item response rates fall below 70%, for Access or Servicing, an
item-level analysis of non-response bias was not necessary. The Access item response rates
range from 84% to 100% with a 96% average while Servicing response rates range from 81% to
100%, with a 95% average.
Table B1.e. Access Item and Total Item Response Rate11
Question Number
1
2
3
4
5a
5b
5c
5d
5e
5f
6
Item Response Rate
93%
99%
98%
99%
99%
99%
99%
98%
97%
98%
100%
Unit Response Rate
20%
22%
22%
22%
22%
22%
22%
22%
21%
22%
22%
11
Open capture question for additional comments about your experience and e-mail opt in questions display “N/A” and were
not included in item and total item response rate calculations
45
Table B1.e. Access Item and Total Item Response Rate (Continued)
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24a
24b
24c
24d
25
26
27
28a
28b
28c
29
30
31
32
33
34
35
97%
98%
95%
100%
94%
98%
98%
97%
99%
99%
100%
99%
97%
97%
98%
98%
97%
97%
97%
94%
98%
99%
99%
97%
96%
95%
97%
99%
96%
98%
N/A
97%
N/A
N/A
21%
22%
21%
22%
21%
22%
22%
21%
22%
22%
22%
22%
21%
21%
22%
22%
21%
21%
21%
21%
21%
22%
22%
21%
21%
21%
21%
22%
21%
21%
N/A
21%
N/A
N/A
46
Table B1.s Servicing Item and Total Item Response Rate12
Question Number
1
2
3
4
5a
5b
5c
5d
5e
5f
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24a
24b
24c
24d
25
26
27
Item Response Rate
92%
100%
98%
99%
99%
99%
99%
98%
98%
98%
88%
96%
99%
94%
93%
99%
98%
81%
96%
91%
98%
N/A
95%
84%
88%
90%
97%
89%
93%
92%
94%
96%
99%
98%
98%
Unit Response Rate
23%
25%
24%
25%
25%
25%
25%
25%
24%
24%
22%
24%
25%
24%
23%
25%
25%
20%
24%
23%
25%
N/A
24%
21%
22%
22%
24%
22%
23%
23%
23%
24%
25%
24%
25%
12
Open capture questions for additional comments about your experience and items unclear in letter and e-mail opt in
questions display “N/A” and were not included in item and total item response rate calculations
47
Table B1.e. Access Item and Total Item Response Rate (Continued)
28
29
30
31
N/A
98%
N/A
N/A
N/A
25%
N/A
N/A
In the item response rate calculations above, JDP considered blanks as non-response for mail
returns and “don’t know” selections in addition to blanks as non-response for online returns.
“Don’t know” selections are included as non-response for online returns since respondents are
forced to select a response in order to continue the survey.
Similarly, “N/A” responses were also included as non-response for rating questions in online
returns. For respondents taking the survey online, the respondent must answer each question
before proceeding to the next question in the survey, “Not Applicable” or “N/A” could either
mean that the respondent was answering “N/A” to the question or did not wish to answer it.
Therefore, this response option was included as non-response.
48
Appendix C
Study Overview
1.1 Study Background
The Voice of the Veteran Satisfaction Initiative tracks Veteran satisfaction with the benefits and
services received from VBA. The Voice of the Veteran Line of Business Tracking Satisfaction
Research Study is ongoing survey research tracking for Veteran satisfaction with VBA’s lines of
business: Compensation, Pension, Education, Vocational Rehabilitation & Employment (VR&E),
and Loan Guaranty (LGY).
As part of Executive Order 13571 Streamlining Service Delivery and Improving Customer
Service, agencies that provide significant services directly to the public are to identify and
survey customers, establish service standards and track performance against those standards,
and benchmark customer service against the best in business. This program enables VBA to
understand what is important to Veterans relative to benefits received and services provided.
This program provides timely and actionable Veteran feedback on how well VBA is providing
services. Insights from this program identify opportunities for improvement and measure the
impact of improvement initiatives, as well as continuously measure performance outcomes.
Compensation’s survey instrument is measures Veterans’ satisfaction with access and receipt of
benefits process. In FY15, fielding occurred continuously on a monthly basis for Access and
annually for Servicing. Surveys remained open in field until the end of each quarter. If any
surveys were received after a quarter closed field, then those returns were counted in the next
quarter’s number of returns.
Methodology
Fielding
Frequency
Total Mailouts
Per Year
Target
Number of
Completes
Access
Mixed – Mail and Online
Monthly
160,000
48,000
Servicing
Mixed – Mail and Online
Annually
60,000
18,000
Survey
1.2 Methodology
The respondents had the option of completing a paper survey or an online survey. Respondents
were first sent a postcard with a link to the eSurvey to complete the survey online. Each
respondent was issued a unique sequence number which is entered online prior to beginning
the eSurvey. Three weeks after deployment of the postcard, a survey packet containing a cover
letter, survey instrument, and Business Reply Envelope (BRE) was sent to non-responders (to
the postcard mailing). The sample for mailings of the survey packet was cleaned to exclude
anyone who completed the survey at least one week prior to the cleaning.
49
1.2.1 Sample Criteria
The targeted populations were identified by Compensation Service. For Compensation Access
the target population is defined as Veterans and beneficiaries who began receiving
compensation benefits six to eighteen months ago. For Compensation Servicing the target
population is defined as Veterans and beneficiaries: (1) who received a decision for their
application for compensation benefits with the past 30 days, (2) those who were found eligible
on a new or subsequent claim and (3) those who have been denied and are not appealing the
decision.
VBA was responsible for providing sample to JDP that meets the following sampling criteria:
Sample Population
Inclusion Criteria
Frequency of Data Request
Access Survey
For Access the target population
includes Veterans and beneficiaries
who began receiving compensation
benefits six to eighteen months ago.
Monthly
Servicing Survey
For Servicing the target population
includes Veterans and beneficiaries:
(1) who received a decision for their
application for compensation
benefits with the past 30 days, (2)
those who were found eligible on a
new or subsequent claim and (3)
those who have been denied and
are not appealing the decision.
Annually
1.2.2 Sample File Generation
Compensation generates the sample files based upon the sampling definitions and submits
sample files directly to BAS.
BAS receives the sample files and sends to VADIR for processing.
VADIR processes sample files (to remove SSN and append demographics/EDIPI) and returns
to BAS.
BAS transfers sample files (via EDX platform) to JDP and notifies JDP via email that sample
files are ready for deployment.
JDP cleans the sample file and selects the sample.
Sample is transferred to Government Printing Office (GPO) print vendor (via EDX platform)
for printing and mailing of the postcards and survey packages.
50
VOV_LOB
Sample is transferred in accordance with the following schedule: Tracking_Production Schedule_10.06.15.pdf
1.2.3 Data Transfer
The sample was posted by BAS once a month within the sampling folder on the VOV EDX site.
Sample should be provided in a file layout consistent with the file layout provided for the study
as outlined below.
Compensation File Layout
ACC_Code
AcillaryDecisionDate
Address_1
Address_2
ADDRESS_LINE_ONE
ADDRESS_LINE_THREE
ADDRESS_LINE_TWO
ADDRESS_LINE3
ADDRESS_LINE4
ADDRESS_LINE5
ADDRESS_LINE6
AGE
AID_ATTENDANCE_HOUSEBOUND
AMOUNT_AWARDED
Award_End_Reason
BENEFICIARY_TYPE
BENEFIT_TYPE
BRANCH_OF_SERVICE
CHAR_SVC_CD
CHARACTER_OF_DISCHARGE
CITY_NAME
Claim_DT
CLAIM_LATEST_STATUS
CLAIM_NUMBER
CLOTHING_ALLOWANCE
CURRENT_CLAIM_STATUS
DATE_OF_APPLICATION
DATE_OF_BIRTH
Date_of_Birth
DATE_OF_BIRTH2
51
Compensation File Layout (Continued.)
DATE_OF_DEATH
DAYS_OF_ACTIVE_SERVICE
DeathIndicator
DIAG_CODE
DISABILITY_RATING
DPBarcode
DPV_Code
Email_Address
ENTITLEMENT_CODE
ENTITLEMENT_DATE
EOD
EVALUATION
GENDER
GENDER_1
HOMELESS
INDIVIDUAL_UNEMPLOYABILITY
LAST NAME
LATEST_END_PRODUCT
NO_OF_APPEALS
NO_OF_DEPENDENTS
NUM_DISABILITIES_CLAIMED
NUM_OF_DEPENDENTS
PAYEE_CODE
PERIOD_OF_SERVICE
PHONE_NUMBER
POA_CD
RAD
REASON_CODE
REGIONAL_OFFICE_CODE
REGIONAL_OFFICE_CODE_1
SERVICE_REPRESENTATIVE
SSN
STATE NAME
ZIP_CODE
Date of Award
Method of Application
Number of Application
Prior Education Level
52
1.2.4 Data Cleaning
JDP processed the sample according to the following cleaning rules:
1. De-duplicate records within each business line and across surveys based on the unique
identifier (EDI_PI or VA_ID) for each record. Note: EDIPI is Electronic Data Interchange
Personal Identifier.
a) Exception: For Pension Access (v1) and Pension Servicing (v8), de-duplicate records
based on EDI_PI and Claim Number.
b) When each new sample file is received, JDP cleans it against all sample selected from
every sample batch that has been delivered 12 months prior to ensure a respondent
does not receive a VA line of business survey more than once in a 12 month-period. In
the case of duplicates occurring within the same sample month, priority is assigned to
business lines with the lowest number of sample records.
2. Clean out records present on the JDP Do Not Contact list and clean against the National
Change of Address (NCOA) list.
3. Clean out any respondents who do not have any EDI_PI or VA_ID included in their sample
record.
a) Exception: For Pension Access (v1) and Pension Servicing (v8), clean out records with
blank EDI_PI and Claim Number.
4. Clean out any respondents not specified as a dependent/spouse who have a date of death
(DOD) in their sample record.
5. Clean out any respondents who do not have any address included in their sample record.
6. Assign and maintain unique sampling identifiers to each sample record in order to track
history of sampling. Exclude records that have been sampled in the past 12 months to
ensure no respondent is mailed surveys more than once in a 12-month timeframe. This rule
may not apply to those who completed a survey.
1.2.5 Sample Cleaning Rules Glossary
Duplicate records in sample file – the record is cleaned out if there is more than one record
within the same sample file for the same respondent
Duplicate record history – The record is cleaned out if the record has been selected within the
past 12 months for any of VBA’s business line surveys (i.e. Compensation, Pension, Education,
Home Loan Guaranty, and Vocational Rehabilitation) regardless of whether the respondent
completed the survey
Invalid address – The record is cleaned out if JDP’s address verification software indicates an
invalid address code
Invalid values – The record is cleaned out if the “VA_ID” field is blank
Blanks – The record is cleaned out if the “Name” field corresponding to the record is blank
Do not contact – The record is cleaned out if the individual is listed on JDP’s Do Not Contact List
53
1.2.6 Sample Selection
JDP selected sample records following the completion of the sample cleaning process. The
following guidelines are referenced when selecting sample:
1. Total Sampling Targets: The table below summarizes the total sampling target per an RO per
a fielding period. The “Sampling Target per RO” column indicates the minimum number of
sample records that should be selected per an RO for each survey. If this minimum target
number cannot be reached for a particular RO, sample from a different RO will be selected
to make up the difference.
Frequency
Total
Sampling
Target
Sampling
Target Per
Time Period
Sampling
Target Per
RO
Number of
ROs
Access
Survey
Monthly
160,000
13,333
300
57
Servicing
Survey
Annually
60,000
60,000
1,053
57
2. The same record cannot be selected for multiple surveys during the same wave.
Respondents who have completed a survey within the past 12 months cannot be selected.
Survey priority is based on the number of records in each sample file. The survey with the
smallest number of records is given first priority.
3. Following sample selection, the JDP project teams receives an automated report confirming
the number of records selected for each survey version. The JDP project team verifies that
the sample selection quantities reflect the sample targets and approves the sample file for
fielding.
1.2.7 Fielding/Sampling Frequency
Survey
Instrument
Access
Survey
Servicing
Survey
Methodology
Total
Survey
Instruments
Targeted
Number of
Completes
Number of
Postcards
(eSurvey)
Number
of Mail
Packages
Fielding
Frequency
Mixed – Mail
and Online
160,000
48,000
160,000
160,000
Monthly
Mixed – Mail
and Online
60,000
18,000
60,000
60,000
Annually
54
1.2.8 Order Generation and Fulfillment Process
Federal Acquisition Regulations (FAR 8.8) mandate government agencies solicit all printing
requirements through the Government Printing Office. GPO utilizes print vendors to fulfill
orders. A Data Transfer Agreement (DTA) must be in place with print vendor and contractor
before BAS can obligate funds or transfer sample files to the print vendor and contractor.
Prior to mailing the postcards and mail surveys, print orders must be generated for each survey.
The entire process may take up to 2-4 weeks from inception of the print order to the mailing of
the survey package or postcard. Below are the steps involved in order generation and order
fulfillment.
Order generation
After sample is received by JDP, the sample files are cleaned and selected. Then Letter Work
Orders (LWOs) are created to provide the print vendor with the necessary information to
match the sample files to the correct survey instrument. (1 day)
JDP creates the print order and sends over to BAS Contractor Officer’s Representative
(COR). (Same day as above step)
The COR then reviews, authorizes, and submits the print order. (1 day)
The BAS Publication Officer and/or COR submits the orders to the VA Publications Services
Division (VAPSD). (Same day as above step)
The order is issued a control number by a VBA Management Analyst, Publications. (Variable
timing)
Once the control number is assigned, the order goes to VA Publication Services Division
liaison to forward to GPO Contracting Officer. (Variable timing) Note: the amount of time an
order is with VAPSD varies greatly, it could be from 3 days up to 20 days.
The GPO Contracting Officer sends the printing and mailing order to the print vendor.
Order fulfillment
Once the order is placed, the GPO print vendor is allotted 9 business days to fulfill the order
(2 days to generate proofs, 2 days for proof review/correction, and 5 days to print and
mail).
Upon receipt of the proofs from print vendor, JDP reviews and approves; then BAS reviews
and approves; then VAPSD reviews and approves.
The GPO Print Vendor then conducts the printing of the instruments and prepares to mail.
The print vendor uses envelopes that were subcontracted.
The GPO Print Vendor mails the postcards and/or survey packages.
After the orders have been mailed, the print vendor provides the mail receipts to
contractor, BAS and VAPSD.
Upon order completion, VAPSD provides actual costs to BAS.
55
1.2.9 Data Collection
During the survey fielding period, both online survey returns and paper surveys are collected as
they are received and posted on a secure EDX site. Responses from paper surveys are scanned
through automated imaging software while verbatim responses are recorded by a live survey
processor. Survey returns must have all pages intact in order to be processed and counted as a
return. Surveys with missing pages are counted as unusable. Returns are also considered
unusable, if there is an indication that the individual completing the survey is not the individual
selected from the sample file (i.e. the respondent name and/or address on the survey is
replaced with a different name and/or address). During each day of fielding, a subset of survey
returns undergo quality assurance to validate the accuracy of responses captured. If duplicate
surveys are returned (as identified by the unique sampling identifier assigned to each sample
record), the original survey return is processed while the duplicate survey is removed. In the
case of duplicate survey returns from mixed methodology surveys, the date the survey was
received is used to identify the original return while the subsequent return is removed postfielding.
1.2.10 Reporting
Reporting occurs four times yearly for the Access survey.
On a quarterly basis, the following deliverables are provided:
Scorecard
Data Matrices
Data is loaded to the VOV reporting site
Open ended comments (verbatims)
On a semiannual (twice yearly) basis, the following deliverable is provided:
Data Analysis and Presentation
Reporting occurs once annually for the Servicing survey.
On an annual basis, the following deliverables are provided:
Scorecard
Data Matrices
Data is loaded to the VOV reporting site
Open ended comments (verbatims)
Data Analysis and Presentation
56
APPENDIX D
Approaches to Mitigating the Effect of NonResponse Bias and Strategies to Improve the
Response Rate
The following section outlines two approaches used in FY 2015 to mitigate the potential of nonresponse bias. As mentioned earlier in the report, J.D. Power affirms that while high response
rates are always desirable in surveys, an 80% response rate is typically not achievable for a
voluntary, customer-satisfaction survey instrument (Malhotra & Birks, 2007), particularly those
that do not provide an incentive (not recommended for this program). To illustrate this point,
the Dillman Method for survey fielding was discussed in Dillman, D. A. (2014) – a survey
instrument was fielded to 600 students at the University of Washington. After 5 attempts to
solicit a response in a closed university setting, as well as offering a monetary incentive to
complete the study, they were only able to garner a 77% response rate.
The first approach to minimize non-response occurs before and during data collection and
involves introducing measures to maximize survey response rates. The second approach is to
make statistical adjustments after the data is collected.
1.1 Approach 1: Strategies to Maximize Response Rates
Prior to, and during, fielding the survey, JDP implemented the following measures to reduce the
chances of non-response:
Respondents were provided with the promise of confidentiality on the survey cover letter
and postcard, and assured that their survey responses would not impact their current or
future eligibility for benefits.
Following the first mailing, non-respondents were sent an additional survey mailing.
Respondents were provided with a toll-free telephone number and dedicated e-mail
address to contact JDP about survey-related inquiries (e.g., how to interpret questions and
response items, the purpose of the survey, how to get another copy of the survey if their
copy has been lost/damaged, etc.). Telephone calls and e-mails are responded to within 24
hours and answered during regular business hours (8:00-5:00pm PT).
JDP ensured the web-based surveys were accessible to people with disabilities by
maintaining 508 compliant standards. These standards include:
Keyboard navigation rather than mouse or other pointing devices
Customization options for color, size, and style of text displayed
Compatibility with screen-readers to translate items displayed on the survey in audible
output and/or Braille displays
Customer support and technical support through JDP Help Desk toll-free phone number
and email address
Exclusion of non-text elements, image maps, animation, flashing or blinking text.
57
The survey fielding period was extended to offer opportunities to respond for subgroups
having a propensity to respond late (e.g., males, young, full-time employed).
The survey was developed and reviewed in order to enhance respondent understanding of
the survey materials and to improve the relevancy of the data collected:
Prior to fielding the Benchmark study, a series of cognitive labs was conducted with test
users to ensure the survey questions were easily understood and correctly interpreted.
Revisions were made to the survey based on test user feedback. (As per OMB Guideline
1.4.1)
After the Benchmark study and prior to fielding the first year of the Tracking study,
Compensation Service and JDP conducted a review of the survey instruments and
modified the surveys to improve the relevancy of data collected. (As per OMB Guideline
1.4.2)
1.2 Approach 2: Correcting Unit Non-response Bias with Sample Weighting and
Survey Raking
As stated above, the two approaches to tackling non-response bias include implementing
measures to maximize response rates during the fielding period and making post hoc statistical
adjustments to the survey results afterwards. The following section discusses the statistical
adjustments approach, which include weighting the data or imputing scores to correct the
amount of non-response bias. An example of this approach would be the survey raking
procedure described earlier in this paper. See the associated references in the “Survey Raking
Procedure for Sample Weightings” section for more information.
The procedure known as “raking” adjusts a set of data so that its marginal totals match
specified control totals on a specified set of variables. The term “raking” suggests an analogy
with the process of smoothing the soil in a garden plot by alternately working it back and forth
with a rake in two perpendicular directions, Izrael and Battaglia (2004).
If non-response bias was identified in the survey data, the non-response bias could be
corrected mathematically with a post-stratification survey weight. JDP would weigh the survey
data based on certain demographics (such as age, gender, region, etc.) of the total sample so
that the weighted survey data would conform more to the demographics of the total sample.
The implicit assumption in this approach is the distributions of characteristics of the nonrespondents within an adjustment class (such as an age group) are the same, on average, as
those of the respondents within the same adjustment class.
See Appendix B for the item response rate for each question in the survey. If the item response
rate was not lower than 70%, as per OMB standards, the imputation of data is not necessary.
In the case that a particular item-level response was less than 70%, JDP would recommend
conducting additional analysis to determine the potential for other factors (i.e. missing or skip
patterns in the survey instrument) to be the cause of non-response.
58
Strategies to Improve Response Rate
In addition to the strategies listed above, JDP recommends considering the following strategies
to improve response rates going forward:
Issue ongoing public communications (e.g. press releases, post information on the VA
website) to spread awareness and confirm the legitimacy of the VA Study.
Educate VA employees and VSOs about the survey to encourage participation. Provide a list
of frequently asked questions and answers to VSOs and VA employees to equip them with
answering Veterans’ questions regarding the survey.
Send e-mail invitations to Veterans rather than mailing postcards to make it easier for
Veterans to complete the survey online.
Reduce the length of the survey to improve respondents’ willingness to respond
Reduce overall number of questions and number of response options for each question.
Increase the number of contacts to respondents with additional reminders about the survey
to encourage participation
Provide respondents with an additional paper survey questionnaire.
Reduce the frequency of mailings to reduce the opportunities for delays and errors in the
GPO Print process.
Revise the cover letter and postcard to express the importance of participation in the
survey.
Provide sample from the 30 day period immediately prior to the mailing rather than sample
from 90 days prior to improve the recency of their experience with the benefit (which
improves both participation and recollection).
Alter the responsibility of sample file generation from Compensation to PA&I. The PA&I
data pull will increase consistency.
Change location of sequence number to directly follow survey link on postcard and cover
letter.
Alter formatting on postcard and cover letter to include color print to make materials more
readable to increase participation.
59
Appendix E
Impact of FAR 8.8
Federal Acquisition Regulation (FAR) 8.8 requires that printing must be conducted through the
Government Printing Office (GPO). The following section outlines limiting factors of the VOV
Line of Business Tracking Satisfaction Research Study that occurred as a result of the FAR
requirement.
Through the utilization of the GPO Print Vendor, the following occurred in FY15:
o Quality issues included:
Survey instruments were printed and mailed:
Utilizing the sample population from one survey, but receiving a different
survey (e.g., potential respondents from the pool of one business line
received the survey for a different business line)
Using a version of the instrument that was outdated; this version did not
contain the current questions or responses that were being fielded
Sent the wrong surveys to the wrong respondents
o Ongoing timeliness delays occurred with each set of orders placed, as the order
fulfillment process took a minimum of 2-4 weeks
1.1
Impact
The project experienced ongoing delays in the printing and mailing of its postcards and survey
packets for VBA’s lines of business. The delays affected the critical processes required to
execute the VOV Program to its fullest potential.
A multitude of quality issues were experienced throughout FY15 that negatively impacted the
VOV Program response rates. The issues that occurred impacted: access to the online survey;
readability of mail materials; level of effort required by respondents to take the survey;
relevancy of survey; and the diminishment of brands (VA/JDP) associated with poor quality
materials.
60
Appendix F
NOTE: Questionnaire is not shown in the formatted version that respondents used to fill out
survey.
Survey Questionnaires
[DO NOT DISPLAY/IDENTIFY SECTION HEADERS. DISPLAY SINGLE QUESTION PER PAGE.]
[RESPONSE CODES APPEAR IN BRACKETS AT THE END OF EACH RESPONSE FOR SINGLE
RESPONSES AND IN THE PROGRAMMING INSTRUCTIONS FOR MULTIPLE RESPONSES.]
Servicing Questionnaire
Benefit Information
1. How did you FIRST learn about VA benefit programs? (Mark only one) If you
are unsure, please indicate the first way you remember learning about VA
benefit programs. [RADIO BUTTONS. SINGLE RESPONSE.]
a. VA website [1]
b.
c.
d.
e.
f.
g.
h.
eBenefits.va.gov [3]
Social media websites (e.g., Facebook, Twitter, etc.) [11]
Internet (excluding VA and social media sites) [14]
Mail (from VA) [4]
VA phone number (800-827-1000) [5]
In person at a Regional Office/Visit from a VA employee [10]
VA medical center/VA Vet Center [8]
i. Transition Assistance Program/Disabled Transition Assistance Program
briefings [6]
j. Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
k. Other Veterans [13]
l. Friends or family [15]
m. Other publications (e.g., Army Times, local newspaper, etc.) [16]
n. Vocational Rehabilitation and Employment Service
o. Other (Specify) ___________________[TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.] [97]
p. Don’t know or not sure [99]
2. What method(s) do you MOST FREQUENTLY use to obtain general
information about VA benefits or services? (Mark all that apply) [CHECK
BOXES. MULTIPLE RESPONSE.CODE EACH RESPONSE AS 0 IF
UNCHECKED OR 1 IF CHECKED]
61
a.
b.
c.
d.
e.
f.
g.
h.
i.
j.
k.
l.
m.
n.
o.
p.
q.
VA website
eBenefits.va.gov
Social media websites (e.g., Facebook, Twitter, etc.)
Other websites (excluding VA or social media sites)
Phone
Mail
E-mail
In person at a Regional Office
VA medical center/VA Vet Center
Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
Disabled Veterans’ Outreach Program
Friends or family
Vocational Rehabilitation and Employment Service
Other publications (e.g., Army Times, local newspaper, etc.)
Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE]
None of the above [MUTUALLY EXCLUSIVE RESPONSE]
3. How frequently would you like to receive communications (e.g., e-mails, letters,
newsletters, etc.) about VA benefits or services? (Mark only one) [RADIO
BUTTONS. SINGLE RESPONSE.]
a. Weekly [1]
b. Monthly [2]
c. Quarterly (every 3 months) [3]
d. Semi-annually (twice per year) [4]
e. Annually (once per year) [5]
f. Never [6]
g. Don’t know or not sure [99]
4. How would you like to receive information from VA about benefits or services?
(Mark all that apply) [CHECK BOXES. MULTIPLE RESPONSE. CODE EACH
RESPONSE AS 0 IF UNCHECKED OR 1 IF CHECKED]
a. Phone
b. Mail
c. E-mail
d. VA website
e. Social media websites (e.g., Facebook, Twitter, etc.)
f. In person at a Regional Office
g. Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
h. Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
i. Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE]
62
The following question asks you to rate various aspects of your experience with
Compensation using a scale of 1 to 10 where 1 is Unacceptable, 10 is Outstanding, and
5 is Average. [SHOW ON SAME PAGE AS THE QUESTION THAT FOLLOWS]
5. When thinking about your most frequently used methods of communication,
please rate your experience in obtaining information about your benefit on the
following items: (Mark only one per row) [SHOW RESPONSES IN GRID WITH
10-POINT SCALE IN COLUMNS AND ATTRIBUTES/RESPONSES IN ROWS
(SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC DETAILS
OF LAYOUT). EVENLY SPACED RADIO BUTTONS/COLUMNS,
ALTERNATE SHADES IN ROWS. SINGLE RESPONSE PER ROW.
RANDOMIZE ALL ATTRIBUTES EXCEPT THE LAST ONE.]
a. Ease of accessing information [ALLOW N/A RESPONSE] [1-10, N/A=99]
b. Availability of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
c. Clarity of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
d. Usefulness of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
e. Frequency of information provided by VA [ALLOW N/A RESPONSE] [110, N/A=99]
f. Overall rating of information [1-10]
Contact with VA
6. During the past 6 months, did you contact anyone from VA about your benefit?
(Mark only one) [RADIO BUTTONS. SINGLE RESPONSE.]
a. Yes [1]
b. No [0]
(Ask Q7-Q12 if Q6 is yes, otherwise go to Q13)
7. Which of the following best describes the reason for your most recent contact?
(Mark only one) [RADIO BUTTONS. SINGLE RESPONSE.]
a. Resolve a problem [1]
b. Ask a question [2]
c. Request a change to your records/provide information [3]
8. Can you briefly describe the nature of your most recent contact? (Mark all that
apply) [CHECK BOXES. MULTIPLE RESPONSE. CODE EACH RESPONSE
AS 0 IF UNCHECKED OR 1 IF CHECKED]
a. Update your dependency status
b. Change your address or direct deposit information
c. Report the death of an individual who received VA benefits
d. Report that you did not receive your VA check or direct deposit
e. Resolve a problem with your benefits
f. Find out about a late benefit payment
g. Report a problem with a VA customer service representative
63
h.
i.
j.
k.
Ask a general question
Obtain information about submitting/re-opening a claim
Check on the status of a claim
Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
9. Thinking about your most recent contact, how did you contact VA? (Mark only
one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Phone [1]
b. Online Chat
c. Website [6]
d. E-mail [7]
e. Mail [9]
f. In person [3]
g. eBenefits.va.gov [10]
10. Was your most recent issue resolved? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE]
a. Yes [1]
b. No [0]
(Ask Q11 if Q10 is No, otherwise go to Q12)
11. Why wasn’t your most recent issue resolved? [CHECK BOXES. MULTIPLE
RESPONSE. CODE EACH RESPONSE AS 0 IF UNCHECKED OR 1 IF
CHECKED]
a. Did not receive all of the information required
b. Received incorrect information
c. Was referred to the incorrect office/person
d. Waiting for follow-up from VA
e. Other (Specify) ____________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
f. Don't know or not sure [MUTUALLY EXCLUSIVE RESPONSE]
12. Thinking of your most recent contact with the VA, how would you rate your
overall customer service experience with the VA or VA representatives using a
scale of 1 to 10 where 1 is Unacceptable, 10 is Outstanding, and 5 is Average?
[SHOW RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND
SINGLE ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR
SPECIFIC DETAILS OF LAYOUT). EVENLY SPACED RADIO
BUTTONS/COLUMNS, SINGLE RESPONSE PER ROW.][1-10]
Benefit Entitlement
64
13. Have you submitted a claim for an increase in your benefit in the past 6
months? (Mark only one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q14 if Q13 is yes, otherwise go to Q22)
14. How did you submit your claim? (Mark only one) [RADIO BUTTONS. SINGLE
RESPONSE]
a. eBenefits.va.gov
b. Mail [1]
c. In person at a Regional Office [2]
d. In person at a Veterans Service Organization (e.g., Amer. Legion, DAV,
VFW, PVA, MOPH, etc.) [3]
e.
f. Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.] [97]
g. Don’t know or not sure [99]
(Ask Q15 if Q13 is yes, otherwise go to Q22)
15. After you submitted your claim, did you receive a notification/confirmation from
VA that your claim was received? [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q16-Q18 if Q15 is Yes, otherwise go to Q19)
16. Thinking about the notification/confirmation from VA, was it clear and easy to
understand? (Mark only one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Not at all clear [1]
b. Somewhat clear [2]
c. Completely clear [3]
d. Don’t know or not sure [99]
e. I did not read the letter [96]
(Ask Q17 if Q16 is “Not at all clear” or “Somewhat clear”, otherwise go to Q18)
17. What did you find unclear/didn’t understand in the notification/confirmation?
(Open Capture) [OPEN-END. TEXT BOX. 1000 CHARACTERS MAX. ALLOW
NO COMMENT, MUTUALLY EXCLUSIVE CHECK BOX. CODE NO
COMMENT AS 0 IF UNCHECKED AND 1 IF CHECKED.]
18. Did you contact VA to obtain clarification about the
notification(s)/confirmation(s)? [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
65
c. Don’t know or not sure [99]
19. Did VA require you to provide additional medical evidence beyond the
information you provided with your original claim? (Mark only one) [RADIO
BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q20 if Q19 is yes, otherwise go to Q22)
20. After you submitted your claim, did VA schedule a medical examination for you
to be re-evaluated? (Mark only one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
d. Not applicable [96]
(Ask Q21 if Q20 is Yes, otherwise go to Q22)
21. Did the exam address your claimed condition(s)? [RADIO BUTTONS. SINGLE
RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
22. Have there been any interruptions to your benefit payments in the past 6
months? (Mark only one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q23 if ‘Yes’ to Q22, otherwise go to Q24)
23. Did you receive a letter notifying you as to the reason why your benefit payment
was interrupted and/or terminated? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
The following question asks you to rate various aspects of your VA experience, using a
scale of 1 to 10 where 1 is Unacceptable, 10 is Outstanding, and 5 is Average. [SHOW
ON SAME PAGE AS THE QUESTION THAT FOLLOWS]
24. Please rate your compensation benefit on the following items: (Mark only one
per row) [SHOW RESPONSES IN GRID WITH 10-POINT SCALE IN
COLUMNS AND ATTRIBUTES/RESPONSES IN ROWS (SEE JDPA
CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC DETAILS OF LAYOUT).
EVENLY SPACED RADIO BUTTONS/COLUMNS, ALTERNATE SHADES IN
ROWS. SINGLE RESPONSE PER ROW. RANDOMIZE ALL ATTRIBUTES
EXCEPT THE LAST ONE.]
66
a. Combined disability evaluation rating percentage (e.g. 10% disabled)
[ALLOW N/A RESPONSE] [1-10, N/A=99]
b. Timeliness of receiving benefit [ALLOW N/A RESPONSE] [1-10, N/A=99]
c. Clarity of your disability rating [ALLOW N/A RESPONSE] [1-10, N/A=99]
d. Overall rating of your benefit payment[1-10]
Overall Experience with Benefit Program
25. Thinking about ALL aspects of your experience with your compensation
benefits, please rate VA overall, using a scale of 1 to 10 where 1 is
Unacceptable, 10 is Outstanding, and 5 is Average. (Mark only one) [SHOW
RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND SINGLE
ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC
DETAILS OF LAYOUT). EVENLY SPACED RADIO BUTTONS/COLUMNS,
SINGLE RESPONSE PER ROW.] [1-10]
Overall Experience with VA
26. Taking into consideration all of the non-medical benefits (e.g., education,
compensation, pension, home loan guaranty, vocational rehabilitation and
employment, insurance, etc.) you have applied for or currently receive, please
rate your experience with VA overall, using a scale of 1 to 10 where 1 is
Unacceptable, 10 is Outstanding, and 5 is Average. (Mark only one) [SHOW
RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND SINGLE
ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC
DETAILS OF LAYOUT). EVENLY SPACED RADIO BUTTONS/COLUMNS,
SINGLE RESPONSE PER ROW.] [1-10]
27. How likely are you to inform other Veterans or beneficiaries about your
experience with VA benefits or services? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE.]
a. Definitely will not [1]
b. Probably will not [2]
c. Probably will [3]
d. Definitely will [4]
28. Do you have any other comments or concerns about your experience? (Open
Capture) [OPEN-END. TEXT BOX. 1000 CHARACTERS MAX. ALLOW NO
COMMENT, MUTUALLY EXCLUSIVE CHECK BOX. CODE NO COMMENT
AS 0 IF UNCHECKED AND 1 IF CHECKED]
67
Additional Questions
29. How are you currently using your benefit payment? (Mark all that apply)
[CHECK BOXES. MULTIPLE RESPONSE. CODE EACH RESPONSE AS 0 IF
UNCHECKED OR 1 IF CHECKED]
a. Rent/mortgage payment
b. Paying bills
c. Paying down debt
d. Medical expenses
e. Education expenses
f. Establishing savings
g. Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
h. Prefer not to answer [MUTUALLY EXCLUSIVE RESPONSE]
i. Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE]
As a reminder, your responses will be kept completely confidential and your e-mail
address will not be sent to VA with any responses on this survey. [SHOW ON THE
SAME PAGE AS THE QUESTION THAT FOLLOWS.]
30. Would you like to provide an e-mail address so VA can contact you with
general information about VA benefits and services? (Mark only one) [RADIO
BUTTONS. SINGLE RESPONSE.]
a. Yes [1]
b. No [0]
c. I do not have an e-mail address [96]
d. Prefer not to answer [98]
(Ask Q31 if Yes in Q30)
31. Please enter your preferred e-mail address where you would like to be
contacted: (Open Capture)
a. E-mail: [TEXT BOX. 100 CHARACTER MAX.]
68
Access Questionnaire
Benefit Information
1. How did you FIRST learn about VA benefit programs? (Mark only one) If you are
unsure, please indicate the first way you remember learning about VA benefit
programs. [RADIO BUTTONS. SINGLE RESPONSE.]
a. VA website [1]
b.
c.
d.
e.
f.
g.
h.
eBenefits.va.gov [3]
Social media websites (e.g., Facebook, Twitter, etc.) [11]
Internet (excluding VA and social media sites) [14]
Mail (from VA) [4]
VA phone number (800-827-1000) [5]
In person at a Regional Office/Visit from a VA employee [10]
VA medical center/VA Vet Center [8]
i. Transition Assistance Program/Disabled Transition Assistance Program
briefings [6]
j. Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
k. Other Veterans [13]
l. Friends or family [15]
m. Other publications (e.g., Army Times, local newspaper, etc.) [16]
n. Vocational Rehabilitation and Employment Service
o. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.] [97]
p. Don’t know or not sure [99]
2. What method(s) do you MOST FREQUENTLY use to obtain general information
about VA’s benefits or services? (Mark all that apply) [CHECK BOXES.
MULTIPLE RESPONSE. CODE EACH RESPONSE AS 0 IF UNCHECKED OR
1 IF CHECKED]
a. VA website
b.
c.
d.
e.
f.
g.
h.
i.
eBenefits.va.gov
Social media websites (e.g., Facebook, Twitter, etc.)
Other websites (excluding VA or social media sites)
Phone
Mail
E-mail
In person at a Regional Office
VA medical center/VA Vet Center
j. Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
k. Disabled Veterans’ Outreach Program
69
Friends or family
Vocational Rehabilitation and Employment Service
Other publications (e.g., Army Times, local newspaper, etc.)
Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.]
p. Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE.]
q. None of the above [MUTUALLY EXCLUSIVE RESPONSE.]
l.
m.
n.
o.
3. How frequently would you like to receive communications (e.g., e-mails, letters,
newsletters, etc.) about VA benefits or services? (Mark only one) [RADIO
BUTTONS. SINGLE RESPONSE.]
a. Weekly [1]
b. Monthly [2]
c. Quarterly (every 3 months) [3]
d. Semi-annually (twice per year) [4]
e. Annually (once per year) [5]
f. Never [6]
g. Don’t know or not sure [99]
4. How would you like to receive information from VA about applying for VA benefits
or services? (Mark all that apply) [CHECK BOXES. MULTIPLE RESPONSE.
CODE EACH RESPONSE AS 0 IF UNCHECKED OR 1 IF CHECKED]
a. Phone
b. Mail
c. E-mail
d. VA website
e. Social media websites (e.g., Facebook, Twitter, etc.)
f. In person at a Regional Office
g. Veterans Service Organizations (e.g., Amer. Legion, DAV, VFW, PVA,
MOPH, etc.)
h. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.]
i. Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE.]
The following question asks you to rate various aspects of your experience with
Compensation using a scale of 1 to 10, where 1 is Unacceptable, 10 is Outstanding,
and 5 is Average. [SHOW ON SAME PAGE AS THE QUESTION THAT FOLLOWS]
5. When thinking about your most frequently used methods of communication
please rate your experience in obtaining information about your benefit
application on the following items: (Mark only one per row) [SHOW
RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND
ATTRIBUTES/RESPONSES IN ROWS (SEE JDPA CONVENTIONS
DOCUMENT PG. 1 FOR SPECIFIC DETAILS OF LAYOUT). EVENLY SPACED
RADIO BUTTONS/COLUMNS, ALTERNATE SHADES IN ROWS. SINGLE
RESPONSE PER ROW. RANDOMIZE ALL ATTRIBUTES EXCEPT THE LAST
ONE.]
70
Ease of accessing information [ALLOW N/A RESPONSE][1-10, N/A=99]
Availability of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
Clarity of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
Usefulness of information [ALLOW N/A RESPONSE] [1-10, N/A=99]
Frequency of information provided by VA [ALLOW N/A RESPONSE] [1-10,
N/A=99]
f. Overall rating of information [1-10]
a.
b.
c.
d.
e.
Contact with VA
6.
During the past 6 months, did you contact anyone from VA about the benefit
application process? (Mark only one) [RADIO BUTTONS. SINGLE
RESPONSE.]
a. Yes [1]
b. No [0]
(Ask Q7-Q12 if Q6 is yes, otherwise go to Q13)
7.
Which of the following best describes the reason for your most recent contact?
(Mark only one) [RADIO BUTTONS. SINGLE RESPONSE.]
a. Resolve a problem [1]
b. Ask a question [2]
c. Request a change to your records/provide information [3]
8.
Can you briefly describe the nature of your most recent contact? (Mark all that
apply) [CHECK BOXES. MULTIPLE RESPONSE. CODE EACH RESPONSE
AS 0 IF UNCHECKED OR 1 IF CHECKED]
a. Change your address or direct deposit information
b. Report the death of an individual who received VA benefits
c. Report that you did not receive your VA check or direct deposit
d. Report a problem with a VA customer service representative
e. Ask a general question
f. Obtain information about submitting/re-opening a claim
g. Check on the status of a claim
h. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.]
9.
Thinking about your most recent contact, how did you contact VA? (Mark only
one) [RADIO BUTTONS. SINGLE RESPONSE.]
a. Phone [1]
b. Online Chat
c. eBenefits.va.gov [10]
d. Website [6]
e. E-mail [7]
f. Mail [9]
g. In person [3]
71
10. Was your most recent issue resolved? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE.]
a. Yes [1]
b. No [0]
(Ask Q11 if Q10 is No, otherwise go to Q12
11. Why wasn’t your most recent issue resolved? [CHECK BOXES. MULTIPLE
RESPONSE. CODE EACH RESPONSE AS 0 IF UNCHECKED OR 1 IF
CHECKED]
a. Did not receive all of the information required
b. Received incorrect information
c. Was referred to the incorrect office/person
d. Waiting for follow-up from VA
e. Other (Specify) ____________________ [TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.]
f. Don't know or not sure
12. Thinking of your most recent contact with the VA, how would you rate your
overall customer service experience with the VA or VA representatives using a
scale of 1 to 10 where 1 is Unacceptable, 10 is Outstanding, and 5 is Average?
[SHOW RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND
SINGLE ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR
SPECIFIC DETAILS OF LAYOUT). EVENLY SPACED RADIO
BUTTONS/COLUMNS, SINGLE RESPONSE PER ROW.][1-10]
Benefit Eligibility and Application Process
13. Thinking about your most recent application, did someone from VA (e.g., call
center representative, regional office representative, etc.) provide you with
information about the benefit application process? [RADIO BUTTONS. SINGLE
RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
14. Thinking about your most recent benefit application, what method did you use to
apply for your benefit? (Mark only one) [RADIO BUTTONS. SINGLE
RESPONSE]
a. eBenefits.va.gov
b. In person at a Regional Office [3]
c. Mail [2]
d. In person at a Veterans Service Organization (e.g., Amer. Legion, DAV, VFW,
PVA, MOPH, etc.) [4]
72
e. Other (Specify) ___________________ [TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.] [97]
f. Don’t know or not sure [99]
15. After you submitted your application, did you receive a notification/confirmation
from VA that your claim was received? [RADIO BUTTONS. SINGLE
REPONSE.]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q16-21 if Q15 is Yes, otherwise go to Q22)
16. Thinking about the notification/confirmation from VA, was it clear and easy to
understand? (Mark only one) [RADIO BUTTONS. SINGLE REPONSE.]
a. Not at all clear [1]
b. Somewhat clear [2]
c. Completely clear [3]
d. Don’t know or not sure [99]
e. I did not read the letter [96]
17. Did you contact VA to obtain clarification about any of the
notifications/confirmations you received? [RADIO BUTTONS. SINGLE
REPONSE.]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
18. Did you provide VA with the documentation that was requested in the
notification(s)/confirmation(s)? (Mark only one) [RADIO BUTTONS. SINGLE
REPONSE.]
a. Yes [1]
b. No [0]
c. Nothing was requested [96]
d. Don’t know or not sure [99]
(Ask Q19-Q20 if Q18 is yes, otherwise go to Q21)
19. How did you submit the documentation to VA that was requested in the
notification/confirmation? (Mark only one) [RADIO BUTTONS. SINGLE
REPONSE.]
a. eBenefits.va.gov
b. In person at a Regional Office [2]
c. Mail
d. Through a Veterans Service Organization(e.g., Amer. Legion, DAV, VFW,
PVA, MOPH, etc.)[3]
e. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.] [97]
f. Don’t know or not sure [99]
73
20. What is your preferred method to submit the documentation to VA that was
requested in the notification/confirmation? (Mark only one) [RADIO BUTTONS.
SINGLE REPONSE.]
a. eBenefits.va.gov
b. In person at a Regional Office [2]
c. Mail
d. Through a Veterans Service Organization (e.g., Amer. Legion, DAV, VFW,
PVA, MOPH, etc.) [4]
e. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.] [97]
f. Don’t know or not sure [99]
21. Did you receive a subsequent notification requesting information in support of
your claim from VA? (Mark only one) [RADIO BUTTONS. SINGLE REPONSE.]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
22. During the application process, did you have to provide the same information
more than once? (Mark only one) [RADIO BUTTONS. SINGLE REPONSE.]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
(Ask Q23 if Q22 is Yes, otherwise go to Q24)
23. What information did you have to provide more than once? (Mark all that apply)
[CHECK BOXES. MULTIPLE RESPONSE. CODE EACH RESPONSE AS 0 IF
UNCHECKED OR 1 IF CHECKED]
a. Discharge papers (DD214)
b. Service treatment records
c. Private medical records
d. Other (Specify) ___________________[TEXT BOX. FORCE TEXT IF
RESPONSE IS SELECTED. 50 CHARACTER MAX.]
e. Don’t know or not sure
The following question asks you to rate various aspects of your experience with your
benefit application using a scale of 1 to 10, where 1 is Unacceptable, 10 is Outstanding,
and 5 is Average. [SHOW ON SAME PAGE AS THE QUESTION THAT FOLLOWS]
24. Please rate your experience with the benefit application process on the following
items: (Mark only one per row) [SHOW RESPONSES IN GRID WITH 10-POINT
SCALE IN COLUMNS AND ATTRIBUTES/RESPONSES IN ROWS (SEE JDPA
CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC DETAILS OF LAYOUT).
EVENLY SPACED RADIO BUTTONS/COLUMNS, ALTERNATE SHADES IN
74
ROWS. SINGLE RESPONSE PER ROW. RANDOMIZE ALL ATTRIBUTES
EXCEPT THE LAST ONE.]
a. Ease of completing the application [ALLOW N/A RESPONSE][1-10, N/A=99]
b. Timeliness of eligibility/entitlement notification [ALLOW N/A RESPONSE] [110, N/A=99]
c. Flexibility of application methods [ALLOW N/A RESPONSE] [1-10, N/A=99]
d. Overall rating of application process [1-10]
(Paper Only Instruction: Ask Q25-Q27 if previously found ineligible for VA benefit
payments, otherwise go to Q28)
25. If you were previously found ineligible for VA benefit payments, did you
understand why you were found ineligible? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
d. Not applicable, never been found ineligible (Online Only Response) [96]
(Online Instruction: Ask Q26-Q27 if Q25 is yes, otherwise go to Q28)
26. Were you provided information about how to appeal your decision? (Mark only
one) [RADIO BUTTONS. SINGLE RESPONSE]
a. Yes [1]
b. No [0]
c. Don’t know or not sure [99]
27. Using a scale of 1 to 10, where 1 is Unacceptable, 10 is Outstanding, and 5 is
Average, please rate the clarity of the information you were provided about
appealing your decision. [SHOW RESPONSES IN GRID WITH 10-POINT
SCALE IN COLUMNS AND SINGLE ROW (SEE JDPA CONVENTIONS
DOCUMENT PG. 1 FOR SPECIFIC DETAILS OF LAYOUT). EVENLY SPACED
RADIO BUTTONS/COLUMNS, SINGLE RESPONSE PER ROW.][1-10]
Benefit Entitlement
The following question asks you to rate various aspects of your experience with your
benefit payment using a scale of 1 to 10, where 1 is Unacceptable, 10 is Outstanding,
and 5 is Average. [SHOW ON SAME PAGE AS THE QUESTION THAT FOLLOWS]
28. Please rate your benefit payment on the following items: (Mark only one per row)
[SHOW RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND
ATTRIBUTES/RESPONSES IN ROWS (SEE JDPA CONVENTIONS
DOCUMENT PG. 1 FOR SPECIFIC DETAILS OF LAYOUT). EVENLY SPACED
RADIO BUTTONS/COLUMNS, ALTERNATE SHADES IN ROWS. SINGLE
RESPONSE PER ROW. RANDOMIZE ALL ATTRIBUTES EXCEPT THE LAST
ONE.]
75
a. Amount of benefit payment [ALLOW N/A RESPONSE][1-10, N/A=99]
b. Timeliness of receiving initial benefit payment [ALLOW N/A RESPONSE] [110, N/A=99]
c. Overall rating of your benefit payment [1-10]
Overall Application Experience
29. Thinking about ALL aspects of your experience applying for your compensation
benefit, please rate VA overall, using a scale of 1 to 10 where 1 is
Unacceptable, 10 is Outstanding, and 5 is Average. (Mark only one) [SHOW
RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND SINGLE
ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC
DETAILS OF LAYOUT). EVENLY SPACED RADIO BUTTONS/COLUMNS,
SINGLE RESPONSE PER ROW.] [1-10]
Overall Experience with VA
30. Taking into consideration all of the non-medical benefits (e.g., education,
compensation, pension, home loan guaranty, vocational rehabilitation and
employment, insurance, etc.) you have applied for or currently receive, please
rate your experience with VA overall, using a scale of 1 to 10 where 1 is
Unacceptable, 10 is Outstanding, and 5 is Average. (Mark only one) [SHOW
RESPONSES IN GRID WITH 10-POINT SCALE IN COLUMNS AND SINGLE
ROW (SEE JDPA CONVENTIONS DOCUMENT PG. 1 FOR SPECIFIC
DETAILS OF LAYOUT). EVENLY SPACED RADIO BUTTONS/COLUMNS,
SINGLE RESPONSE PER ROW.] [1-10]
31. How likely are you to inform other Veterans or beneficiaries about your
experience with VA benefits or services? (Mark only one) [RADIO BUTTONS.
SINGLE RESPONSE.]
a. Definitely will not [1]
b. Probably will not [2]
c. Probably will [3]
d. Definitely will [4]
32. Do you have any other comments or concerns about your experience? (Open
Capture) [OPEN-END. TEXT BOX. 1000 CHARACTERS MAX. ALLOW NO
COMMENT, MUTUALLY EXCLUSIVE CHECK BOX. CODE NO COMMENT
AS 0 IF UNCHECKED AND 1 IF CHECKED]
____________________________________________________
Additional Questions
76
As a reminder, your responses will be kept completely confidential and will not affect
any current or future benefits you may receive. [SHOW ON SAME PAGE AS THE
QUESTION THAT FOLLOWS.]
33. How are you currently using or intending to use your benefit payment? (Mark all
that apply) [CHECK BOXES. MULTIPLE RESPONSE. CODE EACH
RESPONSE AS 0 IF UNCHECKED OR 1 IF CHECKED]
a. Rent/mortgage payment
b. Paying bills
c. Paying down debt
d. Education expenses
e. Establishing savings
f. Other (Specify) ___________________ [TEXT BOX, FORCE TEXT IF
RESPONSE IS SELECTED, 50 CHARACTER MAX.]
g. Prefer not to state [MUTUALLY EXCLUSIVE RESPONSE]
h. Don’t know or not sure [MUTUALLY EXCLUSIVE RESPONSE]
As a reminder, your responses will be kept completely confidential and your e-mail
address will not be sent to VA with any responses on this survey. [SHOW ON THE
SAME PAGE AS THE QUESTION THAT FOLLOWS.]
34. Would you like to provide an e-mail address so VA can contact you with general
information about VA benefits and services? (Mark only one) [RADIO
BUTTONS. SINGLE RESPONSE.]
a. Yes [1]
b. No [0]
c. I do not have an e-mail address [96]
d. Prefer not to answer [98]
(Ask Q35 if Yes in Q34)
35. Please enter your preferred e-mail address where you would like to be contacted:
(Open Capture)
a. E-mail: [TEXT BOX. 100 CHARACTER MAX.]
77
Appendix G
List of Acronyms
AAPOR
ANOVA
BAS
BPA
BRE
CAPS
COR
DTA
EDIPI
EDX
FAR
FY
GPO
ICR
JDP
LGY
LWO
MAR
MCAR
MCMC
MNAR
NPC
OIF
OEF
OMB
OSAT
PA&I
RO
SSN
US
USA
VA
VADIR
VAPSD
VBA
VOV
VR&E
VSO
American Association for Public Opinion Research
Analysis of Variance
Benefits Assistance Service
Blanket Purchase Agreement
Business Reply Envelope
Centralized Account Processing System
Contracting Officer’s Representative
Data Transfer Agreement
Electronic Data Interchange Personal Identifier
Enterprise Data Exchange
Federal Acquisition Regulations
Fiscal Year
Government Printing Office
Information Collection Request
J.D. Power
Loan Guaranty Service
Letter Work Order
Missing At Random
Missing Completely At Random
Markov chain Monte Carlo algorithm
Missing Not At Random
NPC, Inc. Integrated Print and Digital Solutions
Operation Iraqi Freedom
Operation Enduring Freedom
Office of Management and Budget
Overall Satisfaction Index
Office of Performance Analysis & Integrity
Regional Office
Social Security Number
United States
United States of America
Department of Veterans Affairs
VA DoD Identity Repository
VA Publications Services Division
Veterans Benefits Administration
Voice of the Veteran
Vocational Rehabilitation and Employment Service
Veterans Service Organizations
78
| File Type | application/pdf |
| File Title | Training Catalog, Department of Veterans Affairs |
| Subject | Training Catalog |
| Author | Department of Veterans Affairs, Office of Human Resources and Ad |
| File Modified | 2016-12-19 |
| File Created | 2016-12-19 |