App1-Omnibus Household Survey Methodology

Bureau of Transportation Statistics

Survey Documentation for the
Bureau of Transportation Statistics
Omnibus Survey Program
(Public Use)

November 2006

SURVEY DOCUMENTATION FOR THE
BUREAU OF TRANSPORTATION STATISTICS
OMNIBUS SURVEY PROGRAM
(PUBLIC USE)

NOVEMBER 2006

March 12, 2007

TABLE OF CONTENTS
List of Tables ................................................................................................................................. iii
1.

Introduction and Background ..................................................................................................1

2.

Sample Design .........................................................................................................................3
2.1
Target Population ............................................................................................................3
2.2
Sampling Frame and Selection........................................................................................3
2.2.1 RDD Sample ...............................................................................................................4
2.2.2 ID-PLUS .....................................................................................................................4
2.2.3 Address Matching .......................................................................................................5
2.3
Precision of Estimates .....................................................................................................5

3.

Sampling Weights and Adjustments........................................................................................7
3.1
Base Sampling Weights ..................................................................................................7
3.2
Adjustment for Unit Non-Response................................................................................7
3.3
Adjustment for Households with Multiple Telephone Numbers ....................................8
3.4
Adjustment for Number of Eligible Household Members ..............................................9
3.5
Post-Stratification Adjustments.......................................................................................9
3.6
Trimming of Final Analysis Weights............................................................................12

4.

Variance Estimation ..............................................................................................................13
4.1
Variance Estimation Methodology................................................................................13
4.1.1 Software ....................................................................................................................13
4.1.2 Methods.....................................................................................................................13
4.2
Degrees of Freedom and Precision................................................................................14

5.

Data Collection Plan..............................................................................................................15
5.1
Expert Panel ..................................................................................................................15
5.2
Cognitive Interviews .....................................................................................................15
5.3
Data Collection Schedule ..............................................................................................15
5.4
Interview Procedures.....................................................................................................15
5.4.1 Pre-Testing ................................................................................................................15
5.4.2 Interviewer Training .................................................................................................15
5.4.3 Pre-Contact Letter .....................................................................................................18
5.4.4 Call Attempts and Callbacks.....................................................................................19
5.4.5 Disposition Codes .....................................................................................................21
5.4.6 Household Screening ................................................................................................22
5.4.7 Interviewing Methods ...............................................................................................22
5.5
Data Quality Control Procedures ..................................................................................23
5.5.1 Interviewer Performance...........................................................................................23
5.5.2 Other Procedures.......................................................................................................23
5.6
Summary of Data Cleaning ...........................................................................................24
5.7
Treatment of Missing Values ........................................................................................24
i

5.8
Response Rates..............................................................................................................25
5.8.1 Number of Completed Interviews.............................................................................25
5.8.2 Calculation of Response Rates..................................................................................25
5.8.3 Reasons for Non-Response .......................................................................................27
Appendix A: Final Annotated Survey Questionnaire ...................................................................28
Appendix B: Data Dictionary .......................................................................................................47
Appendix C: SAS Formats Library...............................................................................................65
References......................................................................................................................................69

ii

LIST OF TABLES
Table 1:
Table 2:
Table 3:
Table 4:
Table 5:
Table 6:

Census Bureau Regions and Divisions .............................................................................3
Number of Telephone Lines per Household.....................................................................8
Number of Eligible Household Members.........................................................................9
Post-Stratification Cells ..................................................................................................11
Summary of Codes for Missing Values by Data File Format ........................................25
Distribution of Household Cases by Disposition............................................................26

iii

1.

INTRODUCTION AND BACKGROUND

The Bureau of Transportation Statistics (BTS) is conducting a series of monthly surveys to
monitor expectations of and satisfaction with the transportation system and to gather event, issue,
and mode-specific information. The surveys will serve as an information source for the U.S.
Department of Transportation (DOT) modal administrators, who can use them to support
congressional requests, and for internal DOT performance indicators. Overall, the surveys will
support the collection of information on a wide range of transportation-related topics.
This report presents the results of the November 2006 Household Survey, the twenty-fifth of the
monthly household surveys that will be conducted. Each of these monthly surveys will contain a
set of core questions that are based on critical information needs within DOT. In addition,
supplemental questions will be included each month that correspond to one of DOT's five
strategic goals: safety, mobility, economic growth, human and natural environment, and security.
Finally, specific questions posed by the various DOT modes will be included in each survey.
The November 2006 survey collected data from November 6th, 2006 through November 30th,
2006. Data were collected from households in the U.S. using a Random-Digit-Dialed telephone
methodology. The final completed sample size is 1,095 cases, and the total number of variables
in the public-use dataset is 113. The data were collected by MDAC, under contract with the
BTS.
This report provides technical documentation for the November 2006 Household Survey. Its
primary goal is to document background information, sampling procedures, data collection, data
elements and survey variables, response rates, final weights and standard errors estimation.
This report contains the following information:
•

Background of the survey initiative;

•

A detailed description of how sample respondents were selected for the survey;

•

Information regarding the data collection period, the number of completed interviews,
and response rates;

•

Information on interviewer training, pre-testing, interviewing methods, household
screening methods and methods for call attempts and callbacks;

•

Information on the number of cases in the file;

•

Guidance on the use of weights for analyses;

•

Instructions for calculating standard error estimates;

•

The final survey questionnaire;

PAGE • 1

•

A data dictionary that provides the names of survey variables, their codes, labels and the
associated response categories; and

•

A SAS formats library.

PAGE • 2

2.
2.1

SAMPLE DESIGN

Target Population

The target population is the United States non-institutionalized adult population (18 years of age
or older).

2.2

Sampling Frame and Selection

To ensure that the monthly Omnibus Survey conducted in November 2006 and thereafter is
comparable to past Omnibus Surveys (March, 2001 and earlier) the previous methodology was
replicated. The methodology was used to achieve a random sample of non-institutionalized
adults 18 years and older in the fifty states of the United States and the District of Columbia. A
national probability sample of households using list-assisted random digit dialing (RDD)
methodology was employed for the survey. The sample was purchased from GENESYS, a firm
that provides sample for numerous government agencies and the private sector. In summary,
GENESYS initiated a sample development process by first imposing an implicit stratification on
the telephone prefixes using the Census Bureau divisions and metropolitan status (See the
Census Bureau regions and divisions below).
Table 1: Census Bureau Regions and Divisions
REGION
Northeast
Midwest

South

West

DIVISION

STATES

New England

CT, ME, MA, NH, RI, VT

Middle Atlantic

NJ, NY, PA

E. North Central

IN, IL, MI, OH, WS

W. North Central

IA, KS, MN, MO, NE, ND, SD

South Atlantic

DE, DC, FL, GA, MD, NC, SC, VA, WV

E. South Central

AL, KY, MS, TN

W. South Central

AR, LA, OK, TX

Mountain

AZ, CO, ID, NM, MT, UT, NV, WY

Pacific

AK, CA, HI, OR, WA

Within each Census Bureau division, counties and their associated prefix areas located in
Metropolitan Statistical Areas (MSA) were sorted by the size of the MSA. Counties and their
associated prefix areas within a Census Bureau division that are located outside of MSAs were
first sorted by state. Within each state, the counties and their associated prefix areas were sorted
by geographic location. This implicit stratification ensures that the sample of telephone numbers
is geographically representative.
The resulting sample of telephone numbers was address-matched for subsequent mailing of a
pre-contact letter to each address.

PAGE • 3

M. Davis and Company purchased 11,992 telephone numbers for the November 2006 survey. A
total of 7,326 of these numbers were identified as working residential numbers and were divided
into 150 replicates. Each of the 85 fielding replicates released initially contained approximately
50 households. 33 additional replicates were released during Fielding. Eight (8) unused
replicates from November’s sample were used to conduct a pretest. Each pretest replicate had
approximately 50 households. Twenty-four (24) of the 150 November replicates were not
utilized in the actual interviewing, resulting in 5,773 numbers being released for use by the
telephone interviewers.
2.2.1 RDD Sample
To generate the sample the GENESYS System employs list-assisted random digit dialing
methodology. List-assisted refers to the use of commercial lists of directory-listed telephone
numbers to increase the likelihood of dialing household residences. This method gives unlisted
telephone numbers the same chance to be selected as directory-listed numbers.
The system utilizes a database consisting of all residential telephone exchanges, working bank
information, and various geographic service parameters such as state, county, Primary ZIP code,
etc. In addition, the database provides working bank information at the two-digit level – each of
the 100 banks (i.e., first two digits of the four-digit suffix) in each exchange is defined as
"working" if it contains one or more listed telephone households. On a National basis, this
definition covers an estimated 96.4% of all residential telephone numbers and 99.96% of listed
residential numbers. This database is updated on a quarterly basis.
The sample frame consists of the set of all telephone exchanges that meet the geographic criteria.
This geographic definition is made using one or more of the geographic codes included in the
database. Following specification of the geographic area, the system selects all exchanges and
associated working banks that meet those criteria.
Based on the sample frame defined above, the system computes an interval such that the number
of intervals is equivalent to the desired number of sample pieces. The interval is computed by
dividing the total possible telephone numbers in the sample frame (i.e., # of working banks X
100) by the number of RDD sample pieces required. Within each interval a single random
number is generated between 1 and the interval size; the corresponding phone number within the
interval is identified and written to an output file.
The result is that every potential telephone number within the defined sample frame has a known
and equal probability of selection.
2.2.2 ID-PLUS
This process is designed to purge about 75% of the non-productive numbers (non-working,
businesses and fax/modems). Since this process is completed after the sample is generated, the
statistical integrity of the sample is maintained.
The Pre-Dialer Phase – The file of generated numbers is passed against the ID database,
comprised of the GENESYS-Plus business database and the listed household database. Business
numbers are eliminated while listed household numbers are set aside, to be recombined after the
active Dialer Phase.
PAGE • 4

The Dialer Phase – The remaining numbers are then processed using automated dialing
equipment – actually a specially configured PROYTYS Telephony system. In this phase, the
dialing is 100% attended and the phone is allowed to ring up to two times. Specially trained
agents are available to speak to anyone who might answer the phone and the number is
dispositioned accordingly. Given this human intervention in evaluating all call results, virtually
all remaining businesses, non-working and non-tritone intercepts, compensate for differences in
non-working intercept behavior. The testing takes place during the restricted hours of 9 a.m. – 5
p.m. local time, to further minimize intrusion since fewer people are home during these hours.
The Post-Dialer Phase – The sample is then reconstructed, excluding the non-productive
numbers identified in the previous two phases.
2.2.3 Address Matching
The Multi-Source Phone Data Product from Anchor Computer was used for residential reverse
matches (name and address). This file contains approximately 325 million records − all with
name and address information. This file is based on sources that include white page directories,
EDA (Electronic Directory Assistance) Information, Anti-Stalker, and “Little Book”
Information. Each month, Anchor has full file refreshments from their data sources. This is a
full file replacement process − not A/C/D process update, thereby creating a much cleaner
approach. The Anchor file is updated and/or verified monthly. Each new file is incorporated
into the total database as it is received. Anchor’s key data sources run NCOA on a quarterly
basis prior to submitting the data to Anchor.
The data in Anchor’s Phone Database is subjected to a rigorous and routine data hygiene process
to maintain a high level of address completion and deliverability as well as area code correction
and currency. To aid in the accuracy of processing, Anchor runs the client files through an area
code update and correction process to return better, more complete information. Anchor utilizes
vendors that supply clean and current data. Anchor confirms its vendors run the necessary
routines: address standardization (which includes the zip assignment/correction piece), area code
updating/correction, and NCOA processing. Anchor gets the most current data incorporated into
their product upon receipt of file updates.
Anchor Computer, Inc. conducted a residential reverse match (names and addresses) for the
sample provided by GENESYS. Anchor provided an additional 43 matches.

2.3

Precision of Estimates

The precision of estimated frequencies can be assessed by evaluating the width of the 95 percent
confidence interval around the estimates. For this application, the confidence interval can be
approximated for design purposes as:
p s ± Z Var ( p s )
Where

ps is the estimated (sample) proportion;
Z is the 5 percent critical value of the normal distribution; and

PAGE • 5

Var(ps) is the variance of ps.

The calculation of the end points of the confidence interval can be re-written as:

ps ± Z

p s (1 − p s )
n

Or

ps − Z

Where

ps (1 − ps )
≤ P ≤ ps + Z
n

ps (1 − ps )
n

P is the true population value of the proportion; and
n is the sample size.

Therefore, with a sample size of 1,095 and ps = 50 percent, the confidence interval range would
be 47 P 53, approximately.1

1

This method of confidence interval calculation is conservative.
PAGE • 6

3.

SAMPLING WEIGHTS AND ADJUSTMENTS

This section discusses the development of survey weights. Two types of weights were used in
the present survey: inverse-probability weights (to correct for unequal selection probabilities)
and post-stratification (to correct for known discrepancies between the sample and the
population). The final analysis weight reflects both types of adjustments, i.e., adjustment for
non-response, multiple telephone lines, and persons-per-household, and post-stratification
adjustments. The final analysis weight is the weight that should be used for analyzing the survey
data.
The final analysis weight was developed using the following steps:
•

Calculation of the base sampling weights;

•

Adjustment for unit non-response;

•

Adjustment for households with multiple voice telephone numbers;

•

Adjustment for selecting an adult within a sampled household; and

•

Post-stratification adjustments to the target population.

The product of all the above variables represents the final analysis weight. If needed, extreme
values of the final analysis weight can be reduced (or trimmed) using standard weight trimming
procedures.

3.1

Base Sampling Weights

The first step in weighting the sample is to calculate the sampling weight for each telephone
number in the sample. The sampling rate is the inverse of the telephone number’s probability of
selection, or:
WS =

N
n

Where N is the total number of telephone numbers in the population and n is the total number of
telephone numbers in the sample. For this survey, the total number of telephone numbers in the
sampling frame, N, is 280,348,200. The total number of telephone numbers in the sample
(numbers dialed) is 5,688.

3.2

Adjustment for Unit Non-Response

Sampled telephone numbers are classified as responding or non-responding households
according to Census division and metropolitan status (inside or outside a Metropolitan Statistical
Area). The non-response adjustment factor for all telephone numbers in each Census division (c)
by metropolitan status (s), is calculated as follows:

PAGE • 7

ADJ NR =

1
CASRO response rate ( c , s )

Where the denominator is the CASRO response rate for Census division c and metropolitan
status s. The non-response adjustment factor for a specific cell (defined by metropolitan status
and Census division) is a function of the response rate, which is given by the ratio of the
estimated number of telephone households to the number of completed surveys.
The non-response adjusted weight (WNR) is the product of the sampling weight (WS) and the nonresponse adjustment factor (ADJNR) within each Census division / metropolitan status
combination.

3.3

Adjustment for Households with Multiple Telephone Numbers

Some households have multiple telephone lines for voice communication. Thus, these
households have multiple chances of being selected into the sample and adjustments must be
made to their survey weights. The adjustment for multiple telephone lines is:
ADJ MT =

1
Min ( Nb telephone lines, 3)

As shown in the formula, the adjustment is limited to a maximum factor of three. In other
words, the adjustment factor ADJMT will be one over two (0.50) if the household has two
telephone lines, and one over three (0.33) if it has three or more.
The table below provides summary statistics for the number of telephone lines in the monthly
sampled households.

Table 2: Number of Telephone Lines per Household
Mean
Standard deviation
Minimum
25th percentile
Median
75th percentile
Maximum

Value
1.098
0.365
1
1
1
1
4

For respondents that did not provide this information, it is assumed that the household contained
only one telephone line. The non-response adjusted weight (WNR) is multiplied by the
adjustment factor for multiple telephone lines (multiple probabilities of selection) (ADJMT) to
create a weight that is adjusted for non-response and for multiple probabilities of selection
(WNRMT).

PAGE • 8

3.4

Adjustment for Number of Eligible Household Members

The probability of selecting an individual respondent depends upon the number of eligible
respondents in the household. Therefore, it is important to account for the total number of
eligible household members when constructing the sampling weights. The adjustment for
selecting a random adult household member is:
ADJRA = Number of Eligible Household Members
The table below provides summary statistics for the number of eligible members in the monthly
sampled households.

Table 3: Number of Eligible Household Members
Mean
Standard deviation
Minimum
25th percentile
Median
75th percentile
Maximum

Value
1.626
0.749
1
1
2
2
8

For respondents that did not provide this information, a value for ADJRA is imputed according to
the distribution of the number of eligible persons in a household (from responding households)
within the age, gender, and race/ethnicity cross-classification cell matching that of the
respondent for which the value is being imputed.
The weight adjusted for non-response and for multiple probabilities of selection (WNRMT) is then
multiplied by ADJRA, resulting in WNRMTRA, a weight adjusted for non-response, multiple
probabilities of selection, and for selecting a random, household member.

3.5

Post-Stratification Adjustments

Adjusting weighted survey counts so that they agree with population counts provided by the
Census Bureau can compensate for different response rates by demographic subgroups, increase
the precision of survey estimates, and reduce the bias present in the estimates resulting from the
inclusion of only telephone households. The final adjustment to the survey weight is a poststratification adjustment that allows the weights to sum to the target population (i.e., U.S. noninstitutionalized persons 18 years of age or older) by age, gender and race/ethnicity.
The outcome of post-stratification is a factor or multiplier (M) that scales WNRMTRA within each
age/gender/race cell, so that the weighted marginal sums for age, gender and race/ethnicity agree
with the corresponding Census Bureau distribution for these characteristics. The method used in
the post-stratification adjustment is a simple ratio adjustment applied to the sampling weight

PAGE • 9

using the appropriate national population total for a given cell defined by the intersection of age,
gender, and race/ethnicity. 2 The general method for ratio adjusting is:
•

A table of the sum of the weights for each cell denoted by each age, gender, and
race/ethnicity combination is created. Each cell is denoted by S(i,j,k), where i is the
indicator for age, j is the indicator for gender, and k is the indicator for race/ethnicity;

•

A similar table of national population controls is created, where each cell is denoted by
P(i,j,k);

•

The ratio R(i,j,k) = P(i,j,k) / S(i,j,k) is calculated; the cell ratio R(i,j,k) is denoted as the
multiplier M;

•

Each weight, at the record level, is multiplied by the appropriate cell ratio of R(i,j,k) to
form the post-stratification adjustment.

Again, cells used in the post-stratification are defined by the combination of age, gender, and
race/ethnicity. With two categories for gender, six for age and four for race/ethnicity,3 a total of
48 (2x6x4) cells can be used. In any month, some race/ethnicity or, preferably, age categories
may be merged if the number of completed interviews within the corresponding cells falls below
thirty.
For this survey, many of the cells had less than thirty observations. After grouping, and to remain
consistent with what was done in the previous months, a total of 19 cells were used for poststratification. The cells, used to construct post-stratification adjustments for November 2006,
together with the number of sample observations and the national population estimates from the
Census Bureau are shown in the table on the next page.

2

The Census Bureau provides a detailed breakdown of population count by age, gender and race/ethnicity.
The four race/ethnicity categories used for post-stratification purposes are: Hispanic (any race), Non-Hispanic
Black, Non-Hispanic White, and Non-Hispanic Other.
3

PAGE • 10

Table 4: Post-Stratification Cells
CELL
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
N/A

DESCRIPTION
Male - Hispanic (Any Race)
Male - Non-Hispanic Black
Male - Age 18 – 24 - Non-Hispanic White
Male - Age 25 – 34 - Non-Hispanic White
Male - Age 35 – 44 - Non-Hispanic White
Male - Age 45 – 54 - Non-Hispanic White
Male - Age 55 – 64 - Non-Hispanic White
Male - Age 65 or older - Non-Hispanic White
Male - Non-Hispanic Other
Female - Hispanic (Any Race)
Female - Age 18 – 44 - Non-Hispanic Black
Female - Age 45 or older - Non-Hispanic Black
Female - Age 18 – 24 - Non-Hispanic White
Female - Age 25 – 34 - Non-Hispanic White
Female - Age 35 – 44 - Non-Hispanic White
Female - Age 45 – 54 - Non-Hispanic White
Female - Age 55 – 64 - Non-Hispanic White
Female - Age 65 or older - Non-Hispanic White
Female - Non-Hispanic Other
Missing Demographic Information
TOTAL

SAMPLE SIZE
24
35
13
34
67
95
66
81
27
43
30
28
14
49
69
108
96
134
34
48
1,095

POPULATION
14,935,681
11,047,757
8,856,004
11,593,543
13,840,799
15,433,275
11,920,371
12,475,304
7,210,232
14,098,890
7,516,717
6,213,422
8,741,927
11,786,502
14,084,845
15,766,751
12,524,156
16,411,453
7,692,480
N/A
222,150,109

Those respondents who did not supply the demographic information necessary to categorize their
age, gender and/or race/ethnicity are excluded from the post-stratification process and assigned a
value of 1 for M.
The multiplier M is then applied to WNRMTRA to create WNRMTRAPS. However, WNRMTRAPS is
overstated because a portion of the sample is not included in the calculation of the poststratification adjustment. Therefore, a deflation factor is applied to the value of WNRMTRAPS. The
deflation factor DEF is calculated as follows:
6

DEF =

2

4

i =1 j =1 k =1
6

TWNRMTRA_NA +

P(i, j, k)
2

4

P(i, j, k)

i =1 j =1 k =1

Where:
P(i, j, k) is the national population count for cell (i, j, k); and
TWNRMTRA_NA is the sum of the WNRMTRA weights for respondents with missing
demographic information.
This deflation factor denotes the proportion of the target population represented by respondents
with non-missing demographic information. The final analysis weight, WFINAL, is the scaled value
of WNRMTRAPS, calculated as:
PAGE • 11

WFINAL = DEF x WNRMTRAPS
WFINAL can be viewed as the number of population members that each respondent represents.

3.6

Trimming of Final Analysis Weights

Extreme values of WFINAL are trimmed to avoid over-inflation of the sampling variance. In short,
the trimming process limits the relative contribution of the variance associated with the kth unit to
the overall variance of the weighted estimate by comparing the square of each weight to a
threshold value determined as a multiple of the sum of the squared weights. Letting w1, w2, …
wj, denote the final analysis weights for the n completed interviews, the threshold value is
calculated using the following formula:

Threshold = 10

n
j =1

w2j n

1
2

Each household having a final analysis weight that exceeds the determined threshold value is
assigned a trimmed weight equal to the threshold. Next, the age/gender/race cell used in the
post-stratification is identified for each household with a trimmed weight. To maintain the
overall weighted sum within the cell, the trimmed portions of the original weights are reassigned
to the cases whose weights are unchanged in the trimming process.
For cases having trimmed weights but missing age, gender, and/or race/ethnicity information, the
trimmed portions of the original weights are assigned to all remaining cases whose weights are
unchanged in the trimming process.
The entire trimming procedure is repeated on the new set of weights: a new threshold value is
recalculated and the new extreme values are re-adjusted. The process is repeated until no new
extreme values are found.

PAGE • 12

4.

VARIANCE ESTIMATION

The data collected in the Omnibus Household Survey was obtained through a complex sample
design involving stratification, and the final weights were subject to several adjustments. Any
variance estimation methodology must involve some simplifying assumptions about the design
and weighting. Some simplified conceptual design structures are provided in this section.

4.1

Variance Estimation Methodology

The software package SUDAAN® (Software for the Statistical Analysis of Correlated Data)
Version 9.0.0 was used for computing standard errors.

4.1.1 Software
SUDAAN® is a statistical software package developed by Research Triangle Institute to analyze
data from complex sample surveys. SUDAAN® uses advanced statistical techniques to produce
robust variance estimates under various survey design options. The software, in particular, can
handle stratification and the numerous adjustments associated with weights subject to multiple
adjustments.
4.1.2 Methods
Overall, three variables, CENDIV (Census Division), METRO (metropolitan status), and
FNLWGT (final analysis weights), are needed for variance estimation in SUDAAN®. The
method used in the present survey utilizes the variables CENDIV and METRO to create 18 (9x2)
strata, a single stage selection with replacement procedure, and the final analysis weights. This
method provides somewhat conservative standard error estimates.
Assuming a simplified sample design structure, the following SUDAAN® statements can be
used (note that the data file first must be sorted by the variables CENDIV and METRO before
using it in SUDAAN®):

PROC ... DESIGN = STRWR;
NEST CENDIV METRO;
WEIGHT FNLWGT;
More precisely, the following code is used to produce un-weighted and weighted frequency
counts, percentages and standard errors (the variable of interest here is "var1", a categorical
variable with seven levels):

PROC CROSSTAB DATA = datafile DESIGN=STRWR;
WEIGHT FNLWGT;
NEST CENDIV METRO;
SUBGROUP var1;
LEVELS 7;
TABLE var1;
PRINT nsum wsum totper setot / STYLE=nchs;
RUN;
PAGE • 13

When sampling weights are post-stratified, the variance of an estimate is reduced since the totals
are known without sampling variation.4 Using SUDAAN® without any modifications produces
standard errors of estimates that do not reflect this reduction in variance. The estimates of the
standard errors can be improved by using SUDAAN® post-stratification option (POSTVAR and
POSTWGT). This option reflects the reduction in variance due to adjustment to control totals in
one dimension. However, this approach still does not reflect the full effect of post-stratification,
as the other post-stratification dimensions are ignored.5

4.2

Degrees of Freedom and Precision

A typically used rule-of-thumb for degrees of freedom associated with a standard error is the
quantity: number of un-weighted records in the dataset minus number of strata. The rule-ofthumb degrees of freedom for the method above will fluctuate from month to month depending
upon the number of records in each monthly dataset. Most monthly dataset will yield degrees of
freedom of around 1,000.
For practical purposes, any degrees of freedom exceeding 120 is treated as infinite, i.e., if one
uses a normal Z-statistic instead of a t-statistic for testing. Note, that a one-tailed critical t at 120
degrees of freedom is 1.98 while at an infinite degrees of freedom (a 0.025 z-value) is 1.96. If a
variable of interest covers most of the sample strata, this limiting value probably will be adequate
for analysis.

4

For a discussion of the impact of poststratification on the variance of survey estimates see, in particular, "Sampling
and Weighting in the National Assessment," Keith F. Rust and Eugene G. Johnson, Journal of Educational
Statistics, 17(2): 111-129, Summer 1992.
5
For a presentation of SUDAAN®'s handling of poststratification adjustments see "1999 Variance Estimation,"
National Survey of America's Families Methodology Report, 1999 Methodology Series, Report No. 4, prepared by
J.M. Brick, P. Broene, D. Ferraro, T. Hankins, C. Rauch and T. Strickler, November 2000.
PAGE • 14

5.
5.1

DATA COLLECTION PLAN

Expert Panel

An expert panel was not a task for this survey.

5.2

Cognitive Interviews

Cognitive interviews were not a task for this survey.

5.3

Data Collection Schedule

The survey was conducted over 24 days to enable 1,000 interviews to be completed. The survey
period was from November 6 through November 30. Interviews were not conducted on
Thanksgiving.

5.4

Interview Procedures

The following outlines the key phases of the interviewing procedures utilized in the survey.

5.4.1 Pre-Testing
A Pre-Test was conducted prior to the initiation of actual calling. The Pre-Test was used to
replicate the data collection process and identify any problem areas related to the process, the
survey instrument in total, specific questions, answer choices, questionnaire instructions or
question format. It was also used to test the interview length.
Telephone supervisors conducted a total of 26 pre-test interviews (RMA - 9 interviews, and
MDAC - 17 interviews) of the draft survey instrument. All problematic questions, issues and
recommendations resulting from the pre-test were included in the list of problematic issues.

5.4.2 Interviewer Training
All new interviewers initially completed a generic two-day (approximately 12 hours) classroom
training on general interviewing skills. Additionally, each month all interviewers will complete
approximately four to six hours of classroom training on specific aspects of the Omnibus
Household Survey. In response to normal interviewer turnover and/or increased staffing needs,
all interviewers new to the project will receive the full complement of training prior to beginning
their interviewing for this study.
An outline of the generic two-day training is below. This generic training included these topics
as well as Asking questions as worded (Verbatim Reading and Recording), use of bold type on
the screen, use of light type on the screen, use of ALL CAPS on the screen (Maneuvering
through CfMC: Start Interviewing, Meaning/Significance of font style (e.g., bold) and text
effects (e.g., all caps). Also, interviewers were provided with a list of Frequently Asked
Questions so they were ready to counter a respondent’s potential refuse to participate in the
study.

PAGE • 15

I. ORIENTATION
Introduction to M. Davis and Company, Inc.
Welcome
MDAC Way
Organizational Chart
Your Job Description/Responsibilities
Policies and Procedures
II. TRAINING
***Includes Excerpts from the Market Research Association (MRA) Training Manual
A. Introduction to the Marketing and Opinion Research Industry
What is marketing and opinion research?
Types of interviews
Techniques used in data collection
Survey settings
Overview of the marketing and opinion research process
Key Terms
B. The Interviewer’s Role
Appropriate Attitude
Characteristics of a successful interviewer
Recruiting Respondents
The “Art” of Interviewing
Key Terms
C. Respondents
Relating to Respondents
“Training” Respondents
Building and Maintaining Rapport
“Active Listening”
Callback Scenarios and Procedures
Terminations
D. Questions and Answers Plus Other Topics
The One Unbreakable Rule
Types of Questions
The Interviewing Process
Paperwork
Quality Assurance
Dos and Don’ts
Conducting the Interview
Editing the Interview

PAGE • 16

Monitoring (includes Quotas)
Validation
E. Bias, Probing and Clarifying
Introduction
Good Feedback
Bad Feedback
Avoid Bias
Verbatim Reading and Recording
Open-end Questions and Probing
Additional Section, “Bias, Probing and Clarifying”
F. Objections and Refusal Conversion
Nine Most Common Objections and Reasons for Refusal
Acknowledgement of the Objection
Soft Refusal Conversion
G. Getting Familiar With The Computer
Mouse
Keyboard
Logging On
H. Maneuvering through CfMC
Keyboard Commands
Introduction to CfMC Phone System
Starting the Interviewing
Interviewing with SURVENT
Responding to Different Question Types
SURVENT Commands
More About CfMC
Role Playing
I. Open Discussion
Additional questions
Each survey month, a questionnaire update training is conducted to discuss the questionnaire
changes. An updated interviewer training manual specific to the new month is developed and
distributed to the interviewers. An outline of the approximately four-to-six hour training
includes:
•

A review of last month’s results;

•

Feedback from interviewers, supervisors;

•

Problems and issues emerging from last month’s data collection;

PAGE • 17

•

An Overview of changed sections from last month (Sections B, S and M);

•

Question-by-Question Training for New Sections.

In addition to the initial (generic) training
interviewer re-training is conducted on an
replaced or the survey instrument changes.
needed for improvement or changes in work
control procedures.

and monthly refresher (survey-specific) training,
“as-needed” basis – that is, as interviewers are
Also, interviewers are evaluated and retrained as
habits as identified by our monitoring and editing

On a monthly basis MDAC reviews the new questionnaire for changes, incorporates any changes
approved by BTS emanating from the Expert Panel Review, the Cognitive Interviews and the
Pretest. MDAC re-issues a new manual to each interviewer with the changes.

5.4.3 Pre-Contact Letter
Eight (8) calendar days prior to the start of data collection a BTS-approved pre-contact letter is
sent to sample numbers with an address. The intent is for each household with an address to
receive the pre-contact letter several days before they receive a call to conduct the interview.
There were 1,842 advance letters sent out on November 4, 2006. The percentage of addresses
available for the sample was 41.2 percent.
An “800” number is listed in each letter with the specific times to call (M-F, 9 a.m. – 11 p.m.
EST; Sat and Sun, 1 p.m. to 9 p.m. EST). The letters are categorized by call center and each call
center’s “800” number. Should the respondent call outside the times listed above they will
receive a phone message asking them to leave their name and number and someone will contact
them as soon as possible to conduct the interview.
The toll free number is also mentioned at the first, seventh, fourteenth and every nth attempt in
messages left for potential respondents with an answering machine in cases where we are unable
to make contact with a member of the household. Additionally, the 1-800 number is left to
arrange an appointment for an interview.
A message is not left after each attempt when encountering an answering machine due to
concern that people might avoid the call or feel “harassed” if they were away for a few days and
find four to six messages on their answering machine upon returning home. Given that a
household with an answering machine is called two to three times per day during the Omnibus
Household Survey there must be a balance between perceived harassment and encouraging
participation, particularly given the limited duration of fielding.
A study of telephone practices published in January 2000 by the Council for Marketing and
Opinion Research (CMOR) found no conclusive data showing that leaving a message on an
answering machine for a respondent is effective. This study states that only 17% of the
telephone centers surveyed left a message on the answering machine. Of the call centers which
did leave a message 75% left an 800 number, 71% left a message on the first call and 62% left a
message on subsequent calls.
PAGE • 18

Given the short time frame for data collection, the potential perception of harassment and prior
research results, MDAC believes the best approach is to leave the toll free 800 number at the
first, seventh, fourteenth and twentieth calls.

5.4.4 Call Attempts and Callbacks
The interviews are conducted using CfMC computer assisted telephone interviewing software.
At a minimum, one thousand (1,000) interviews are completed each month. The interviewing is
distributed between two call facilities, Robinson Muenster Associates and MDAC.
Robinson Muenster Associates (RMA) has two shifts Monday through Friday (9 a.m. – 5: 30
p.m. and 5:30 p.m. – 9:30 p.m.), on Saturdays 10 a.m. – 5 p.m. and Sundays 1 p.m. – 9 p.m.
MDAC has two shifts Monday through Friday (9 a.m. – 5p.m. and 5 p.m. – 12 midnight) and two
shifts on Saturdays (11 a.m. – 5 p.m. and 5 p.m. – 11 p.m.) and Sundays (11 a.m. – 5 p.m. and 5
p.m. – 11 p.m.). Monday through Friday, 9 a.m. to 2 p.m., only callbacks (scheduled and nonscheduled) are initiated at both RMA and at MDAC due to historically documented significantly
lower completion rates during this time period. In addition, calls after 9 p.m. local time are for
scheduled callbacks only. No non-scheduled callbacks are conducted after 9 p.m. local time.
In 2001, numbers were sent to each call center to initiate the calling. Each month the amount of
numbers released initially by each call center was based on the calling experiences of previous
months related to improving the response rate. Additional numbers released during the ten day
calling period was based upon past calling history, the quantity of numbers determined to be
ineligible, and projection of completes based upon past and current experience, number of
callbacks achieved and refusal conversion rates.
In January 2002, the number release protocol was modified. Since that month, all the numbers to
be dialed in a month are released on the first day of calling, and no additional numbers are
released during the ten-day calling period. This revised protocol facilitates more dials per
number released and has in part contributed to the higher response rates experienced since
January 2002 compared to previous months of calling.
When a phone number is called initially, the interviewer determines that it is a household. Then
the interviewer requests to speak with an adult 18 years of age or older (if the person on the
phone is not an adult). Once an adult is on the line, then the interviewer randomly selects the
actual survey respondent by asking for the adult in the household who had a birthday most
recently. When the adult with the most recent birthday comes onto the phone line the
interviewer conducts the survey. Should the interviewer not be able to complete the survey the
following dispositions are recorded:

Do-Not-Call dispositions are for households that request their number not be called in the future.
This disposition ensures compliance with the respondent’s request.
Refusals are defined as when a person refuses to participate in the survey at all. Someone who
breaks off the interview or refuses because s/he doesn’t have time or says s/he is busy is
considered a callback. Refusals are routed to supervisors and selected interviewers capable of
converting refusals into completions or other disposition. Interviewers experiencing a refusal
PAGE • 19

enter the appropriate refusal code. Supervisors review refusals the next day and assign the
refusal numbers to the appropriate personnel to initiate callbacks with a refusal script. Refusal
households are called twice a day, once during the time period contact was initially made and
one other time period. The refusal callback is rotated between the morning and late afternoon
time periods from Monday through Friday.
Callbacks are scheduled and prioritized by the CfMC software. The callbacks are prioritized
based upon the following criteria: first priority – scheduled callback to qualified household
member; second priority – scheduled callback to “qualify” household (includes contact with
Spanish language barrier households); third priority – callback to make initial contact with
household (includes answering machine, busy, ring no answer); and fourth priority – callbacks
that are the seventh or higher attempts to schedule interview.
An interview is considered “complete” only if all questions are answered. A refusal to answer an
individual question meets the definition of, and counts as, an “answered” question.
Should the interviewer not be able to complete the interview the following procedures will be
followed:

Scheduled callbacks can be dialed at anytime during calling hours and as frequently as
requested by the callback household up to seven times. Callback attempts in excess of seven are
at the discretion of the interviewer based upon his/her perception of the likelihood of completing
the interview. The basis of the interviewer’s perception, in part, is determined by how
vigorously the interviewer is being encouraged to call back to complete the interview by the
potential respondent or another member of the household. The interviewer then confers with a
supervisor and a final determination is made as to if the interviewer continues calling.
Callbacks to Spanish language households are conducted by Spanish-speaking interviewers.
Interviewers who identify a household as Spanish speaking alert the supervisor a Spanishspeaking interviewer is needed to handle the phone call. If the Spanish interviewer is not
available, the interviewer will inform the respondent someone will call back, then record as CBS
(Callback Spanish). If the person is not available within the next hour a callback will be
scheduled, if possible.
Those records identified as Spanish will be routed to a Spanish-speaking interviewer. The
Spanish Interviewer makes the call and follows the standard protocol for all English calls.

Callbacks for initial contact with potential respondents are distributed across the various
calling time periods and weekday/weekend to ensure that a callback is initiated during each time
period each day. Two (Saturday and Sunday) to three (Monday through Friday) callbacks per
number are initiated per day assuming the number retains a callback status during the calling.
There are up to twenty (20) callback attempts. This protocol is designed for ring no answer and
answering machines. When an interviewer reaches a household with an answering machine
during the seventh, fourteenth or twentieth time calling the interviewer leaves a message with the
respective appropriate 800 number.

PAGE • 20

Callbacks to numbers with a busy signal are scheduled every 30 minutes until the household is
reached, disposition is modified, maximum callbacks are achieved or the study is completed.
In July 2002, six codes were added to the In-Scope section, and will be kept for future months.
These codes are: NAQ - No Answer Qualified, BZQ - Busy Qualified, AMQ - Answering
Machine Qualified, LMQ - Left Message Qualified, CCQ - Cannot Complete Call Qualified, and
PMQ - Privacy Manager Qualified. These codes were added to ensure that In-Scope Callbacks
remain in the In-Scope category even when subsequent calls led to dispositions such as No
Answer, Busy, Answering Machine, Left Message, Cannot Complete Call and Privacy Manager.

5.4.5 Disposition Codes
The following are the disposition codes used for each call outcome:
Out-of-Scope Numbers:
• BG – Business (The number dialed is a non-residential phone number. The call is
terminated and the number resolved.)
• CF – Computer/Fax (The number dialed has led to a modem, fax, pager, or cell phone.)
• DS – Disconnected number (The number dialed is disconnected. The call is terminated
and the number resolved.)
• NC – Number change (The call yielded a recording that the number was changed, with or
without a change in the area code.)
• NQ – No one 18 years old or older in household
• UNB – Unavailable before and during study period
Scope Undetermined:
• NA – No answer (The phone is not answered within 5 rings.)
• BZ – Busy (busy signal)
• AM – Answering machine (The call has led to an answering machine or voicemail.)
• LM – Left message (on the 7th, 14th and 20th calls)
• CCC – Cannot complete call (The message “Your call cannot be completed at this time”
is received. This is a message provided by the local telephone company when there is a
line problem in the local area. These calls are dialed on another day.)
• PM – Privacy manager (Privacy manager is a feature provided by local telephone
companies that requires incoming callers to identify themselves, before the household
will accept the call.)
• NQL – Eligibility undetermined because of language problems or deafness
• RFI – Refused to speak with interviewer (screening incomplete) If the respondent refuses
to speak with interviewer prior to answering F1020 (screening incomplete) and, if asked,
F1010 responded “no”
• HRI – Requests their name be removed from calling list or if the respondent refuses to
speak with interviewer for second time prior to answering F1020 (screening incomplete)
and, if asked, F1010 responded “no”
• OD – The maximum number of call attempts is reached before being able to determine
eligibility
PAGE • 21

•
•

CBU – Callback undetermined
CSU – Callback spanish undetermined

In-Scope Numbers:
• YES – Yes (Respondent has agreed to be screened and is eligible, 18 years old or older.)
• NAQ – No answer qualified
• BZQ – Busy qualified
• AMQ – Answering machine qualified
• LMQ – Left message qualified
• CCQ – Cannot complete call qualified
• PMQ – Privacy manager qualified
• CB – Callback (The respondent has asked that we call them back at another time.)
• CBS – Callback Spanish
• DL – Deaf/Language (The respondent is eligible but is hard of hearing, or cannot speak
English fluently to complete the interview.)
• RFQ – Respondent refusal (Respondent refuses after establishing there is a qualified
household member by answering F1050 or a later appearing question, or after answering
F1010 “yes”.)
• UN – Unavailable (Was available when study began or unable to determine.)
• DR – Respondent deceased prior to completion of interview
• AC – The area code is changed but not the number
• HRQ – Requests their name be removed from calling list or respondent refusal for second
time after establishing there is a qualified household member by answering F1050 or a
later appearing question, or after answering F1010 "yes"
• DIP – Reinterview deletion, ineligible person in household interviewed
• DDA – Reinterview deletion, discrepancy in answers during reinterview
5.4.6 Household Screening
Qualified respondents are at least 18 years of age or older and must be the household member
with the next birthday. If the household member is not available at the time of the call a callback
is scheduled to screen and/or interview the respondent.
5.4.7 Interviewing Methods
Incentives were not offered to potential respondents in exchange for their participation in the
survey. Surveys were conducted in both English and Spanish. If the potential respondent refuses
to be interviewed the reason for refusal is recorded. The average length of the interview was 10
to 12 minutes and an additional 3 to 5 minutes to screen and recruit potential respondents.
Generally, interviewers introduced themselves, who they worked for, the purpose of the survey,
and assured the potential respondent this was not a sales call. Interviewer then determined
whether there was an eligible person in the household. Once contact was made with the eligible
household member the interviewer they reintroduced themselves when necessary, explained the
purpose of the survey, that it is a voluntary study, indicates the survey takes only 10 minutes,
indicated all information would remain confidential and they can refuse to answer any question.
PAGE • 22

If the potential respondent agrees to participate the interviewer provides the respondent an
opportunity to ask any questions, addresses their questions and the interview is conducted.
However, if it is not a convenient time then a callback is scheduled.

5.5

Data Quality Control Procedures

A key component to successful data quality control procedures is a well-trained and experienced
interview staff. All potential interviewers underwent intensive training and orientation
regardless of their level of experience prior to being hired for this project. New hires were first
screened on their voice quality, diction, and their ability to administer a simple test
questionnaire.
Our interviewer training for administering telephone surveys included:
•
•
•
•
•
•
•
•

Orientation on the purpose and importance of marketing research, company policies, and
quality standards including viewing Market Research Association (MRA) training
videotapes;
Testing on material developed by the Market Research Association;
Background and purposes of the survey;
Procedure for selection of correct respondent for the interview;
Intensive hands-on training on the "basics" of interviewing itself- the handling of skip
patterns, probing and clarify techniques, sample administration, Computer Assisted
Telephone Interviewing (CATI), overcoming refusals, etc.;
Observing and listening to experienced interviewers conducting actual interviews during
which each trainee's performance is closely monitored and evaluated under actual
interviewing conditions;
Constant reference on the importance of accuracy, quality and courtesy; and
Successful completion of a total of approximately eight hours of training during the
different sessions.

5.5.1 Interviewer Performance
Ongoing monitoring of every interviewer is undertaken throughout the BTS Omnibus Survey.
Fifteen (15%) to twenty (20%) percent of all calls are monitored. An interviewer evaluation
form is completed for each monitored contact with a household. Additionally, the evaluation
forms includes two to three evaluations of a completed interview per hour. The evaluation forms
are paper hard copy forms and are available for review by BTS at the offices of M. Davis and
Company, Inc. in Philadelphia.
5.5.2 Other Procedures
The initial two days of interviews by each interviewer are checked to identify any problems
administering the survey. The objective is to identify problems, if any, correct the errors and
take action so that the problems do not reappear. Before beginning the second day of work all
interviewers are alerted to their problems, if any, and the interviewers review how to ensure the
problem does not recur. Interviews that were completed during the second day are checked to
see that the first day’s errors are not repeated. If errors were repeated and dependent upon the
PAGE • 23

significance of the error, the interviewer is retrained and/or removed from the project for that
month of calling.
Newer interviewers are monitored at a higher rate regardless of their level of experience until
their first performance evaluation. Additionally, reinterviewing is performed on 10% - 20% of
each interviewer's work through actual callbacks to respondents to verify responses to key
questions. The reinterviewing is initiated on the second day of interviewing to ensure early
detection of problems and to avoid a backlog of calls. Reinterviewing is performed for both new
and experienced interviewers.

5.6

Summary of Data Cleaning

On a daily basis, the data file is checked as a standard to maintain quality. The CfMC utility
called SCAN, allows for checking the data, to be sure that all questions are being asked in
accordance with the skip patterns on the final questionnaire. The file is also checked for missing
codes.
This survey contains “other specify” questions. These questions allow the interviewer to record
text responses that do not appear on the pre-listed set of responses. “Other specify” responses
are edited to determine if responses entered in “other specify” appear on the pre-listed set of
responses. Upon review of the “other specify” responses, it may be necessary to “code-back” a
response to the pre-list. This occurs when an interviewer recorded a response as “other”,
although one of the pre-listed responses matched the “other” response.

5.7

Treatment of Missing Values

As with any survey, the BTS Omnibus Survey, by design, contains questions that are not asked
of certain respondents based on their response(s) to other questions. In addition, there will
always be some respondents who do not know the answer to or chose not to answer some
questions in the survey. Each of these responses can have a different meaning to the data user.
While each of these response categories is important in characterizing the results of the survey,
they are often removed from certain analyses, particularly those involving percentages.
Therefore, the categories were given standard codes for easy identification. The table below
presents the response categories and how they are represented in each data file.

PAGE • 24

Table 5: Summary of Codes for Missing Values by Data File Format
Dataset Formats
Response Category
SAS ®
SAS ®
Microsoft
Text Comma
Excel
Delimited
Version 9.1 Transportable
Appropriate skip
.S
.S
-7
-7

SPSS
-7

Refused

.R

.R

-8

-8

-8

Don't know

.D

.D

-9

-9

-9

5.8

Response Rates

The procedures for response rate calculation are based on the guidelines established by the
Council of American Survey Research Organizations (CASRO) in defining a response rate.

5.8.1 Number of Completed Interviews
A total of 1,095 interviews were completed during the survey period.
5.8.2 Calculation of Response Rates
The final response rate for the survey is obtained using the following formula:

Response Rate =

Completed HH Interviews
HHs In Scope + Scope Undetermined *

HHs In Scope
HHs In & Out of Scope

The table below presents the distribution of household telephone numbers by disposition
categories. The number of household cases in each category was then used in the above formula
to calculate an overall response rate of 48.46 percent.

PAGE • 25

Table 6: Distribution of Household Cases by Disposition
Disposition Category

Number of
Households

Telephone Numbers Available
5,773
Telephone Numbers Released
5,668
Telephone Numbers Not Dialed
0
Telephone Numbers Dialed
5,668
Out-of-Scope Numbers (Ineligible)
2,237
BG - Business
455
CF - Computer/Fax
483
DS - Disconnected number
1,227
NC - Number change
32
NQ - No one 18 years old or older in household
10
UNB - Unavailable before and during study period
30
Scope Undetermined
1,948
NA - No answer
655
BZ - Busy
104
AM - Answering machine
244
LM - Left message
91
CCC - Cannot complete call
3
PM - Privacy manager
4
NQL - Eligibility undetermined because of language problems or deafness
37
RFI - Refused to speak with interviewer (screening incomplete)
308
HRI - Hard refusal *
367
OD - Maximum call attempts reached
0
CBU - Callback Undetermined
130
CSU - Callback Spanish Undetermined
5
In-Scope Numbers
1,483
Complete
1,095
Partial Complete
10
DIP - Reinterview Deletion, Ineligible Person in Household Interviewed
0
DDA - Reinterview Deletion, Discrepancy in Answers during Reinterview
1
CB - Callback
76
CBS - Callback Spanish
29
NAQ - No Answer Qualified
61
BZQ - Busy Qualified
4
AMQ - Answering Machine Qualified
28
LMQ - Left Message Qualified
0
CCQ - Cannot Complete Call Qualified
11
PMQ - Privacy Manager Qualified
0
DL - Deaf/Language
74
RFQ - Respondent refusal
7
UN - Unavailable
35
DR - Respondent deceased prior to completion of interview
2
AC - The area code is changed but not the number
0
HRQ - Hard refusal *
50
CASRO Response Rate
48.46%
* Note: Beginning in March 2002, and for all future months, to more accurately reflect the breadth of cases that fall
within the HRI and HRQ categories the words “Hard Refusal” have replaced the words “Requested name be
removed from calling list”.

PAGE • 26

For the Omnibus survey the following is undertaken to maximize the response rate:
1. Matching sample telephone numbers against commercial file against residential
directory-listed numbers.
2. Advance letter stating clearly the aims, objectives and importance of the survey, with toll
free number to callback. MDAC will collaborate with BTS to create a BTS approved
advance letter.
3. Coordination of the mailing of advance letters with the interview calling.
4. Develop answers for the questions and objections that may arise during the interview.
5. Leaving message on answering machine with a toll free number.
6. Having multi-lingual interviewers to reduce language barriers.
7. Elimination of non-residential numbers from sample.
8. Callbacks of respondents who initially refused or broke-off interview.
9. Minimizing turnover of key and non-key personnel.

5.8.3 Reasons for Non-Response
As with any survey, the BTS Omnibus Survey, by design, contains questions that ask
respondents to supply the demographic information necessary to categorize their age, gender,
and/or education. There will always be some respondents who do not choose to answer some
questions in the survey. For respondents that did not want to provide this information, the most
common reasons for non-responses are: I don’t like giving my age, I would rather not say, I don’t
like to be labeled, and that is personal information.
Common reasons for non-responses when asked questions regarding contacts they may have had
with any government agencies and/or why they contacted the agencies are: I don’t want to say
because I don’t trust the government, I don’t want to answer because I have an issue pending,
and I would rather not say.

PAGE • 27

APPENDIX A: FINAL ANNOTATED SURVEY QUESTIONNAIRE
Section F – Introduction and Respondent Selection
[PHONE NUMBER]
USE AUTODIALER
BYPASS AUTODIALER

1
2

F1000.
Hello, my name is _______ and I’m calling on behalf of the United States
Department of Transportation. We’re conducting a survey on transportation issues
including security of the transportation system, commuting to work and congestion. Your
household has been randomly selected for this study and your opinions will help to
strengthen our nation’s transportation system. Your participation in this study will only
take about 10 minutes. There is no penalty for refusing to answer any question. This study
is authorized by law and your answers will only be used for statistical purposes. By law
your responses will be kept confidential and will not be disclosed to anyone other than
employees and contractors of this study.
READ IF NECESSARY:
Title 49, Section 111c2 of the United States Code requires that no penalty be
associated with refusing to answer any question.

Title 49, Section 111 (i) of the United States Code requires that your responses be
kept confidential.
Title 18, Section 1905 of the United States Code states that everyone working on this
study is subject to a jail term and/or fine if he or she makes public ANY information
that could identify you.
F0080.

Have I reached you at [telephone number]?
1) Yes
2) No – I am very sorry, I must have dialed incorrectly. Thank you, goodbye.

F1010. Are you a member of this household and at least 18 years old?
YES
1 (go to F1030)
NO
2
BUSINESS ADDRESS
3 (go to F1140)

PAGE • 28

F1020. May I speak to a member of this household who is at least 18 years old?
AVAILABLE
1 (go to F1000)
NOT AVAILABLE
2 (MAKE APPOINTMENT)
When would be a good time to call back?
THERE ARE NONE
3 (go to F1140)
F1030. Is this phone number used for...
home use
1
home and business use, or
2
business use only
3
(If 3) – I am very sorry; I’m trying to reach a residence. Thank you.
Goodbye.

F1040. Including yourself, how many people aged 18 or older currently live in this
household?
[IF NEEDED: "Include people who usually stay in this household, but are
temporarily away on business, vacation, or in the hospital. Do not include persons
who are away on full-time active military duty with the armed forces, students living
away from home in their own apartment, or any other family member who may be
in a nursing home or other institution."]
|___|___|# OF ADULT HH MEMBERS
Sample Selection
IF THERE ARE NO ADULT HH MEMBERS, GO TO F1140.
IF ONLY 1 ADULT IN HH, GO TO F1080. OTHERWISE, RUN RESPONDENT
SELECTION ALGORITHM.
IF 2 ADULTS IN HH, GO TO F1081. OTHERWISE IF RESPONDENT WAS
SAMPLED, GO TO F1080.
OTHERWISE, IF MORE THAN 2 ADULTS IN HH AND RESPONDENT
WAS NOT SAMPLED, CONTINUE WITH F1050.

F1050. The computer has randomly determined that one of the [F1040 answer minus 1]
adults other than yourself should be selected for the rest of the interview. To help us select
this person, do you know who has the NEXT birthday among these adults?
YES
1
NO
2 (go to F1070)
PAGE • 29

F1060. Other than yourself then, which adult has the NEXT birthday?
(A FIRST NAME IS SUFFICIENT IF IT UNIQUELY IDENTIFIES THE HH
MEMBER. IF NEEDED--“We need some way to ask for this person should we need
to call back. If you prefer, just give me that person’s gender and age.”)
NAME AND AGE: __________________________________________________
OR
GENDER:
MALE ... ...1
AND
AGE: |___|___|
FEMALE.......2
(Go to f1110).
SELECTION ALGORITHM:
If N=1, then the screener respondent is selected. End selection process.
If N>1, then, randomly sample the screener respondent with probability equal to 1/N (via
CATI programming). If the screener respondent is selected, then end the selection
process.

F1070.

So that the computer can choose someone to interview, please tell me the first
names and ages of the [FILL # FROM F1040 MINUS 1] adults
currently living in
this household. Please do not include yourself.
[IF NEEDED: "Include people who usually stay in this household, but are
temporarily away on business, vacation, or in the hospital. Do not include persons
who are away on full-time active military duty with the armed forces, students living
away from home in their own apartment, or any other family member who may be
in a nursing home or other institution."]
IF NOT OBVIOUS, ASK: "Is {NAME} male or female?"
IF R ANSWERS DK OR RF TO IDENTIFY HH MEMBERS, EXIT INTERVIEW.
FIRST NAME
GENDER
AGE
MALE ............ 1
___________________________
FEMALE........ 2
|___|___|
MALE ............ 1
___________________________
FEMALE........ 2
|___|___|
MALE ............ 1
___________________________
FEMALE........ 2
|___|___|
(Run selection algorithm on HH members listed in f1070 to select extended respondent. Then, go to f1110).

PAGE • 30

F1080. What is your first name?
NAME: _________________________________________________________
GENDER:

MALE ...........1
FEMALE.......2

AND

AGE: |___|___|

(Skip to question F1120)

F1081 This study is designed to select one household adult to answer the questions. The
computer has chosen the other adult in the household to participate in the next part
of the study. What is the other adult’s name? }
PROBE FOR INFORMATION THAT UNIQUELY IDENTIFIES THE HH MEMBER
SELECTED.
NAME: _________________________________________________________
GENDER:

MALE ...........1
FEMALE.......2

AND

AGE: |___|___|

(If extended respondent = screener respondent, go to F1120. Otherwise, continue.)

F1110. {(HH MEMBER) has been selected to participate in the next part of the
study.} May I speak to (HH MEMBER}?
AVAILABLE ..................................................................... 1 (Go to F1130)
NOT AVAILABLE ............................................................ 2 (MAKE APPOINTMENT)
F1120. Your participation in this study will only take about 10 minutes. There is no
penalty for refusing to answer any question. This study is authorized by law and
your answers will only be used for statistical purposes. By law your responses
will be kept confidential and will not be disclosed to anyone other than
employees
and contractors
of this study.
(skip to question M1000)
F1130. Hello, my name is _______ and I’m calling on behalf of the U.S Department of
Transportation. We’re conducting a survey on transportation issues and would like
to include your opinions and experiences. Your participation in this study will only
take about 10 minutes. There is no penalty for refusing to answer any question.
This study is authorized by law and your answers will only be used for statistical
purposes. By law your responses will be kept confidential and will not be disclosed
to anyone other than employees and contractors of this study.

PAGE • 31

READ IF NECESSARY:
Title 49, Section 111c2 of the United States Code requires that there no penalty be
associated with refusing to answer any question.

Title 49, Section 111 (i) of the United States Code requires that your responses be
kept confidential.
Title 18, Section 1905 of the United States Code states that everyone working on this
study is subject to a jail term and/or fine if he or she makes public ANY information
that could identify you.
(skip to question M1000)
GO TO NEXT SECTION.
F1140. Those are all of the questions that I have. If you have questions about
transportation issues or just want some information, you can call 1-800-6050270, email questions to [email protected] or visit the www.bts.gov/omnibus web site
for additional information. Thank you for your time today.

PAGE • 32

M=Mode Use Questions
M1000.

First I’d like to ask about the types of transportation you use during a
TYPICAL WEEK. We are defining a typical week beginning on Sunday
ending the following Saturday.
HIT “RETURN” TO CONTINUE

Note to Programmer: CATI program should ensure response is less than 8
M1010.

During a typical week, on how many DAYS do you drive or ride in a car,
van, SUV, pickup truck, RV or motorcycle?
ENTER NUMBER
____DAYS

M1020.

During a typical week, on how many DAYS do you travel by taxi or
limousine?
ENTER NUMBER
____DAYS

M1030.

During a typical week, on how many DAYS do you use public
transportation?
ENTER NUMBER
____DAYS

M1040.
outdoors for

During a typical week, on how many DAYS do you ride a bicycle
any reason? ENTER NUMBER
____DAYS

PAGE • 33

J=Journey to Work Items
J1000.

The next questions are about traveling to and from work.
HIT “RETURN” TO CONTINUE

J1010.

LAST WEEK, did you work for pay OUTSIDE YOUR HOME?
1)
Yes
(Skip to question J1030)
2)
No

J1020.

.

LAST WEEK, did you perform any volunteer work OUTSIDE YOUR
HOME?
1) Yes
(Skip to question J1035)
2) No
(Skip to question T1000)

INTERVIEWER READ: For the next questions, please use your main job. By main
job we mean the one at which you usually work the most hours.
J1030.

LAST WEEK, on how many DAYS did you travel from home to work?
_____ days ENTER NUMBER
CATI program should ensure that response is less than 8.
(Skip to question J1040)
INTERVIEWER READ: For the next question, please use your main volunteer work
place. By main volunteer work place we mean the one at which you usually work the
most hours.

J1035.

LAST WEEK, on how many DAYS did you travel from home to your
volunteer work place?
_____ days ENTER NUMBER
CATI program should ensure that response is less than 8.
(Skip to question J1045)

PAGE • 34

J1040.

LAST WEEK, which of the following types of transportation did you use
while traveling from home to work? Did you: READ LIST
01) drive alone in a company vehicle
02) drive with others in a company vehicle
03) drive alone in a non-company vehicle
04) drive with others in a non-company vehicle
05) drive or ride in a carpool or vanpool
06) ride a bus
07) ride a subway
08) ride a train
09) ride a ferry
10) ride a bicycle
11) walk
INTERVIEWER: Do not include short walks, e.g.
from the house to the car/parking lot to the office.
12) Used some other mode (SPECIFY)

YES
1
1
1
1
1
1
1
1
1
1
1

1

NO
2
2
2
2
2
2
2
2
2
2
2

2

______________________________________________
(Skip to question J1050)
J1045.

LAST WEEK, which of the following types of transportation did you use
while traveling from home to your volunteer work place? Did you:
READ LIST

01) drive alone in a company vehicle
02) drive with others in a company vehicle
03) drive alone in a non-company vehicle
04) drive with others in a non-company vehicle
05) drive or rode in a carpool or vanpool
06) ride a bus
07) ride the subway
08) ride a train
09) ride a ferry
10) ride a bicycle
11) walk
INTERVIEWER: Do not include short walks, e.g.
from the house to the car/parking lot to the office.
(12) Used some other mode (SPECIFY)
______________________________________________

YES
1
1
1
1
1
1
1
1
1
1
1

1

NO
2
2
2
2
2
2
2
2
2
2
2

2

PAGE • 35

J1050.
(IF J1020=1, INTERVIEWER SHOULD READ: Please consider “work” as
your main volunteer work place.)

LAST WEEK, how would you rate the level of traffic congestion on your
commute to work? READ LIST
1) Very congested
2) Moderately congested
3) Slightly congested
4) Not at all congested
Now I’d like to ask you about your commute to work over the LAST 12 MONTHS.
J1060.

Thinking about the LAST 12 MONTHS, have you done any of the following
to improve your commute to work? Have you: READ LIST
Yes
No
1) Changed your schedule or work hours to improve your commute
1
2
2) Moved to a home closer to work to improve your commute
1
2
3) Moved to a home closer to public transportation to improve your commute
1
2
4) Changed jobs or left a job to improve your commute
1
2
5) Changed office locations to improve your commute
1
2
6) Worked at home instead of your usual work site to improve your commute
1
2
7) Paid to use a toll road or toll lane to improve your commute
1
2
8) Made any other change to improve your commute?
1
2
(SPECIFY:____________________________________)

J1070. Again, thinking about the LAST 12 MONTHS, would you say the traffic
congestion on your commute to work has gotten much better, somewhat better,
stayed about the same, gotten somewhat worse, or gotten much worse?
1) Much better
2) Somewhat better
3) Stayed about the same
4) Somewhat worse
5) Much worse
(If J1020=1, skip to T1000)
PAGE • 36

J1080.

Is at least part of the work that you do in your main job something you could
do at home?
1)
2)

Yes
No

(Skip to T1000)

J1090.

Does your main employer allow workers to sometimes work at home instead
of coming into the work place?
1)
Yes
2)
No
(Skip to T1000)

J1100.

LAST WEEK, did you work at home instead of traveling to your usual
workplace of your main job? This does not include taking work home at
night or over the weekend, working at home while sick, or self-employed
persons who work at home.
1)
Yes
2)
No
(Skip to T1000)

J1110.

LAST WEEK, on how many days did you work at home instead of going to
your usual workplace of your main job?
(CATI programmed to accept less than 8.)
_______ Days

CATI programmed to bring up Comment Box if J1040 had any 1 “Yes” responses and J1110 has
“7” as a response. The interviewer says: You stated that you commuted to the workplace of
your main job last week, and you worked from home for your main job for 7 days last
week. Please tell me why you commuted and worked from home during the same day(s).
TYPE COMMENT:

PAGE • 37

J1120.

What is your primary reason for working at home instead of traveling to
your usual work place of your main job? DO NOT READ LIST.
01) Convenience (INTERVIEWER PROBE: Why is working at home more
convenient?)
02) Saves the company money
03) Saves me money
04) Saves me time
05) To avoid congestion
06) Allows me to take care of family members/be home when kids come home
07) I don’t live in the same area as the company I work for
08) I work for multiple businesses
09) I get more work done at home
10) For health reasons—disability reasons
11) Lack of transportation
12) Any other reason:
(SPECIFY:___________________________________________)

PAGE • 38

T1000.

T=TSA Items
The next few questions are about commercial air travel.
HIT “RETURN” TO CONTINUE

T1010

During the LAST 12 MONTHS, which is since November of 2005, have you
flown on a commercial airline?
1)
Yes
2)
No
(Skip to T1160)

T1020.

During October 2006 did you fly on a commercial airline?
1) Yes
2) No (Skip to T1040)

T1030.

How many DAYS in October 2006 did you fly on a commercial airline?
ENTER NUMBER
____days

T1040.

In what month and year was your most recent commercial airline flight that
departed from a U. S. airport?
INTERVIEWER: PLEASE PROMPT FOR MONTH AND YEAR
ENTER MONTH AND YEAR
_________________MONTH
_____________YEAR
(skip to question T1160 if before November 2005)

T1050.

Please let me verify your last answer as [insert respondent’s last answer].
1)
Yes, correct - CONTINUE
No, incorrect
2)

Please think about your MOST RECENT FLIGHT that departed from a U.S. airport.
T1060.

For your most recent flight, how long did you wait in line to get to the first
passenger security screening checkpoint where you walked through a metal
detector and your carry-on items were x-rayed. Don’t include the time
required to get through the checkpoint—ONLY the time you waited in line to
get to the checkpoint. How long did you wait?
_____ hours and_____ minutes
CATI system must ensure entry for both hours and minutes—cannot have zero for
both fields.
CATI system to ask for verification if more than 4 hours 59 minutes.
Interviewer probe/comment: You mentioned a wait of more than 4 hours,
please consider the question reads: “how long did you wait in line to get to
the first passenger security screening checkpoint where you walked through
a metal detector and your carry-on items were x-rayed. Don’t include the
time required to get through the checkpoint—ONLY the time you waited in

PAGE • 39

line to get to the checkpoint.”
information into open-end box.

Probe why wait was so long and enter

T1070.

For your most recent flight, how satisfied were you overall with your
experience at the passenger security screening check point? Were you READ
LIST
1)
Very satisfied
2)
Satisfied
3)
Dissatisfied
4)
Very dissatisfied

T1080.

For your most recent flight, thinking about the amount of time you spent
waiting in line to get to the passenger security screening checkpoint, would
you say that it was READ LIST 1-5
1)
2)
3)
4)
5)
6)

T1090.

For your most recent flight, how satisfied were you with the time it took to
screen you and your carry-on items? This is the length of time
between placing your carry-on items on the x-ray table and exiting
the security screening area in the direction of the boarding gates. This does
not include the time you spent waiting in line to get to the passenger security
screening checkpoint. READ LIST
1)
2)
3)
4)

T1100.

Much shorter than expected
Shorter than expected
About what you expected
Longer than you expected
Much longer than you expected
You had no expectation INTERVIEWER: DO NOT READ

Very satisfied
Satisfied
Dissatisfied
Very dissatisfied

For your most recent flight, were you selected for additional screening at the
passenger security screening checkpoint such as body wand screening and/or
a body pat-down?
INTERVIEWER: READ IF NEEDED: A body wand search is when a hand
held electronic device in the shape of a slender stick is held very close and
moved over the front, back and sides of your body. A body pat down is when
the front, back and sides of your body are lightly hand patted for the purpose
of detecting something concealed under your clothing.
1)
Yes
2)
No
PAGE • 40

T1110.

For your most recent flight, would you say the passenger screening you
experienced at the security checkpoint was… READ LIST
1)
2)
3)

T1120.

Excessive
Appropriate
Inadequate

For your most recent flight, how satisfied were you with the courtesy of the
screeners at the passenger security screening checkpoint? READ LIST
1)
2)
3)
4)

Very satisfied
Satisfied
Dissatisfied
Very dissatisfied

T1130. How informed do you feel you are about passenger security screening procedures?
Are you READ LIST

1)
2)
3)
4)
T1140.

Very well informed
Moderately well informed
Slightly informed
Not at all informed

Where have you received information about the airport passenger security
screening process?
DO NOT READ LIST--RECORD ALL ANSWERS

1)
2)
3)
4)
5)
6)
7)
8)
9)
10)
11)

Transportation Security Administration website
My own travel experience
Airline or travel agent website
Placed a call or email to the airline
Placed a call or email to a travel agent
Printed material such as a brochure or pamphlet
Signs displayed at airport
Radio, television or newspaper
Friends, family, word of mouth
None of the above
Some other source: SPECIFY: __________________________

INTERVIEWER: (RECORD ANY COMMENT IN T1150 THAT COULD NOT BE
CATEGORIZED AS “Other” IN QUESTION T1140) EXAMPLE : “CHANGES SO
OFTEN WHY BOTHER TO CHECK” or “NO ONE CAN EVER GIVE YOU A
STRAIGHT ANSWER” or “I TRAVEL SO OFTEN I KNOW THE PROCESS”
PAGE • 41

T1150.
Comment _________________________________________________________
Questions T1160, T1170 and T1180 are asked of all respondents including those that have not
flown in the last 12 months.
T1160

How confident are you in the ability of the flight crew to keep air travel
secure and to defend the aircraft and its passengers from individuals with
hostile intentions? READ LIST
1)
2)
3)
4)
5)
.

T1170.

No confidence
A small amount of confidence
A moderate amount of confidence
A great deal of confidence
Total confidence

How would you describe your level of confidence in the ability of the
passenger screeners to keep air travel secure? READ LIST
1)
2)
3)
4)
5)

T1180.

No confidence
A small amount of confidence
A moderate amount of confidence
A great deal of confidence
Total confidence

If cell phones did not interfere with airplane communications systems, do you
think that passengers should be allowed to use their cell phones during a
flight? READ LIST
1)
2)
3)
4)
5)

Definitely should
Probably should
Not sure
Probably should not
Definitely should not

PAGE • 42

D=Demographic Questions
D1000.

This final section asks for information to help us summarize the study
results. No identifying information about you or your household will ever be
released or published.
HIT “RETURN” TO CONTINUE

D1010.

How many vehicles are owned, leased, or available for regular use by the
people who currently live in your household? Please be sure to include
motorcycles, mopeds, and RVs?
ENTER NUMBER ______
(INTERVIEWER: IF RESPONDENT ANSWERS 10 OR MORE, RECORD AS
10)

D1020.

Do you have a medical condition that makes it difficult to travel outside the
home?
1)
Yes
2)
No

D1040.

Please tell me the month and year you were born.
______________MONTH
_______________YEAR
CATI system make sure the respondent is at least 18 years of age
CATI system ask for interviewer to verify if respondent is 100 or greater.
CATI system to match age with F1060 or F1070 if age is entered.
INTERVIEWER: If respondent refuses, use the question below to attempt to get
their age. If I read some age ranges, would you be willing to stop me when I
get to the category that includes your age? INTERVIEWER: READ LIST
UNTIL RESPONDENT STOPS YOU.

1)
18 to 24
2)
25 to 34
3)
35 to 44
4)
45 to 54
5)
55 to 64
6)
65 to 74
7)
75 or older
CATI system to match age category with F1060 or F1070 if age is entered
D1050.

Are you male or female?
RECORD GENDER; ASK ONLY IF NECESSARY
1) Male
2) Female
PAGE • 43

D1060.

Do you consider yourself to be Hispanic or Latino?
1) Yes
(If “Yes”, INTERVIEWER MUST READ: “People who identify themselves
as Hispanic or Latino origin May be of any race.”) (INTERVIEWER
READ ONLY IF NEEDED: “Origin can be viewed as the heritage,
nationality group, lineage, or country of birth of the person or the
person’s parents or ancestors before their arrival in the United States.”)
2) No

D1070.

Is the racial group that best describes you READ ENTIRE LIST. READ
PARENTHETICAL ONLY IF RESPONDENT ASKS FOR CLARIFICATION.
RECORD ALL THAT APPLY
1)
2)
3)
4)
5)

D1080.

What is the highest level of education you’ve completed?
DO NOT READ LIST
1)
2)
3)
4)
5)
6)

D1090.

White
Black
American Indian, Aleut or Eskimo
Asian or Pacific Islander
Other – SPECIFY ____________

Less than high school graduate
High school graduate (or GED)
Some college (or technical vocational school/professional business school)
Two-year college degree (AA: Associate in Arts)
Four-year college degree (BA or BS: Bachelor of Arts/Science degree)
Graduate degree (Master’s, Ph.D., Lawyer, Medical Doctor)

Please stop me when I reach the category that includes your household’s total
annual income for last calendar year, that is, 2005: READ LIST UNTIL
RESPONDENT STOPS YOU TO SELECT A CATEGORY
1)
2)
3)
4)
5)
6)
7)

Under $15,000
From $15,000 to less than $30,000
From $30,000 to less than $50,000
From $50,000 to less than $75,000
From $75,000 to less than $100,000
From $100,000 to less than $125,000
$125,000 or more

PAGE • 44

D1160.

How many home telephone numbers do you have in your household? Please
do not count numbers for cell phones, or phone lines that are used
exclusively for business purposes, computers or fax machines.
1) One
2) Two
3) Three
4) Four or more

D1170

READ AFTER RESPONDENT HAS GIVEN ANSWER: “So, you have ______
phone numbers that are not used exclusively for business, computers, fax
machines or cell phones?”

D1180.

In order to classify your household for statistical purposes, what is your ZIP
code? ENTER NUMBER
___ ___ ___ ___ ___

D1190.

Did your household receive an advance notice in the mail concerning this
study?
1)
2)
3)

D1200.

Yes
No
Not sure

This concludes the study questions. On behalf of the United States
Department of Transportation, I thank you for your time. Goodbye.
HIT “RETURN” TO CONTINUE

PAGE • 45

Interviewer Close Out Questions
THESE QUESTIONS ARE ANSWERED BY THE INTERVIEWER AFTER THE
RESPONDENT HANGS UP.
I0050. HOW WELL DID THE RESPONDENT SEEM TO UNDERSTAND THE
QUESTIONS?
Not at all
1)
2)
Not very well
3)
Well
4)
Very well
I0100. HOW COOPERATIVE WAS THE RESPONDENT IN ANSWERING THE
QUESTIONS?
1)
Not at all cooperative
2)
Not very cooperative
3)
Cooperative
4)
Very cooperative
I0150. IN WHAT LANGUAGE WAS THE INTERVIEW CONDUCTED?
1)
English
2)
Spanish
3)
Both English and Spanish
8)
Other - SPECIFY __________________
PLEASE NOTE ANYTHING ELSE YOU FEEL IS HELPFUL OR IMPORTANT ABOUT
THIS INTERVIEW. CONTINUE TO ENTER TEXT OF RESPONSE
99)
No notes to add

PAGE • 46

APPENDIX B: DATA DICTIONARY
Question
Code

M1010

M1020

M1030

Variable
Name

Variable Label

Response
Category

Response Category Description

Type

Length

Format

Char

6

$TEXTVAR

CASEID

Case Identification Number

METRO

MSA Inside Outside

1
2

MSA area
Non-MSA area

Num

8

MSAINOUT

CREGION

Census Region

1
2
3
4

Northeast
Midwest
South
West

Num

8

CENSREG

CENDIV

Census Division

1
2
3
4
5
6
7
8
9

New England
Middle Atlantic
East North Central
West North Central
South Atlantic
East South Central
West South Central
Mountain
Pacific

Num

8

CENSDIV

DVERSION
INLNGTH

Database Version
Interview Length - Minutes

Year - Quarter

Char
Num

6
8

$TEXTVAR
FORNUM

M1010

Personal Vehicle - Days

_______ days
Don't know
Refused

Num

8

FORNUM

.D
.R

_______ days
Don't know
Refused

Num

8

FORNUM

.D
.R

_______ days
Don't know

Num

8

FORNUM

.D

M1020

M1030

Taxi or Limousine - Days

Public Transportation - Days

PAGE • 47

Question
Code

M1040

Variable
Name

M1040

Variable Label

Response
Category

Response Category Description

Type

Length

Format

.R

Refused
_______ days
Don't know
Refused

Num

8

FORNUM

.D
.R

Bicycle - Days

J1010

J1010

Working Outside Home

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

J1020

J1020

Volunteering Outside Home

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1030

J1030

Travel to Work - Days

_______ days
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

_______ days
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

J1035

J1035

Travel to Volunteer - Days

J1040

J1040A

Work - Company Vehicle - Alone

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040B

Work - Company Vehicle - With Others

1
2
.D

Yes
No
Don't know

Num

8

YESNO

PAGE • 48

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

.R
.S

Refused
Appropriate skip

Type

Length

Format

J1040

J1040C

Work - Non-company Vehicle - Alone

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040D

Work - Non-company Vehicle - With Others

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040E

Work - Carpool or Vanpool

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040F

Work - Bus

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040G

Work - Subway

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040H

Work - Train

1
2
.D

Yes
No
Don't know

Num

8

YESNO

PAGE • 49

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

.R
.S

Refused
Appropriate skip

Type

Length

Format

J1040

J1040I

Work - Ferry

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040J

Work - Bicycle

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040K

Work - Walk

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040L

Work - Other Mode

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1040

J1040M

Work - Specified Other Mode

Verbatim response

Char

250

$TEXTVAR

J1045

J1045A

Volunteer - Company Vehicle - Alone

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045B

Volunteer - Company Vehicle - With Others

1

Yes

Num

8

YESNO

Text

PAGE • 50

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

Type

Length

Format

J1045

J1045C

Volunteer - Non-company Vehicle - Alone

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045D

Volunteer - Non-company Vehicle - With Others

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045E

Volunteer - Carpool or Vanpool

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045F

Volunteer - Bus

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045G

Volunteer - Subway

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045H

Volunteer - Train

1

Yes

Num

8

YESNO

PAGE • 51

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

Type

Length

Format

J1045

J1045I

Volunteer - Ferry

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045J

Volunteer - Bicycle

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045K

Volunteer - Walk

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045L

Volunteer - Other Mode

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1045

J1045M

Volunteer - Specified Other Mode

Verbatim response

Char

250

$TEXTVAR

J1050

J1050

Traffic

Very congested
Moderately congested
Slightly congested
Not at all congested
Don't know

Num

8

TRAFFICA

Text
1
2
3
4
.D

PAGE • 52

Question
Code

J1060

Variable
Name

J1060A

Variable Label

Commute Improving - Changed Schedule / Work
Hours

J1060

J1060B

Commute Improving - Moved Closer to Work

J1060

J1060C

Commute Improving - Moved Closer to Public
Transportation

Response
Category

Response Category Description

Type

Length

Format

Num

8

YESNO

.R
.S

Refused
Appropriate skip

1

Yes

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

1

Yes

Num

8

YESNO

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

J1060

J1060D

Commute Improving - Changed / Left a Job

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1060

J1060E

Commute Improving - Changed Office Locations

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1060

J1060F

Commute Improving - Worked at Home

1
2

Yes
No

Num

8

YESNO

PAGE • 53

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

.D
.R
.S

Don't know
Refused
Appropriate skip

Type

Length

Format

J1060

J1060G

Commute Improving - Used a Toll Road / Lane

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1060

J1060H

Commute Improving - Made Other Change

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1060

J1060I

Commute Improving - Specified Other Change Made

Verbatim response

Char

250

$TEXTVAR

J1070

J1070

Traffic - Change Over the Last 12 Months

1
2
3
4
5
.D
.R
.S

Much better
Somewhat better
Stayed about the same
Somewhat worse
Much worse
Don't know
Refused
Appropriate skip

Num

8

TRAFFICB

J1080

J1080

Work Home - Possible

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

J1090

J1090

Work Home - Allowed

1
2
.D

Yes
No
Don't know

Num

8

YESNO

Text

PAGE • 54

Question
Code

Variable
Name

Variable Label

J1100

J1100

Work Home - Last Week

J1110

J1110

Work Home - Last Week - Days

J1120

J1120A

Work Home - Reason

J1120

J1120B

Work Home - Other Reason

T1010

T1010

Commercial Airline - Last 12 Months

Response
Category

Response Category Description

Type

Length

Format

.R
.S

Refused
Appropriate skip

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

_______ days
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S
1
2
3
4
5
6
7
8
9
10
11
12
.D
.R
.S

Convenience
Saves the company money
Saves me money
Saves me time
To avoid congestion
Take care of family
Live in the different area as the company
Work for multiple businesses
More work done home
Health / disability reasons
Lack of transportation
Other
Don't know
Refused
Appropriate skip

Num

8

HOMEY

Verbatim response

Char

250

$TEXTVAR

Yes
No
Don't know
Refused

Num

8

YESNO

Text
1
2
.D
.R

PAGE • 55

Question
Code

Variable
Name

Variable Label

T1020

T1020

Commercial Airline - October 2006

T1030

T1030

Commercial Airline - October 2006 - Days

T1040

T1040

T1040

T1040A

T1040B

T1040C

Response
Category

T1050

Format

Num

8

YESNO

_______ days
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

_______ month
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

_______ year
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

Num

8

TRIPTIME

6
4
.D
.R
.S

Enter month and year
Less than three months ago
More than three months ago but less than one
year ago
One year ago
More than one year ago
Don't know
Refused
Appropriate skip

1
2
.D
.R
.S

Yes, correct
No, incorrect
Don't know
Refused
Appropriate skip

Num

8

YESNO

Most Recent Flight - Year

Most Recent Flight - Verification

Length

Yes
No
Don't know
Refused
Appropriate skip

1
2
3

T1050

Type

1
2
.D
.R
.S

Most Recent Flight - Month

Most Recent Flight - When

Response Category Description

PAGE • 56

Question
Code
T1060

T1060

T1060

Variable
Name
T1060A

T1060B

T1060C

Variable Label

Response
Category

Most Recent Flight - Screening Wait - Hours

T1070

T1070

Most Recent Flight - Screening - Overall Satisfaction

T1080

T1080

Most Recent Flight - Screening Wait - Satisfaction

Format

Num

8

FORNUM

_______ minutes
Don't know
Refused
Appropriate skip

Num

8

FORNUM

.D
.R
.S

Calculated

Num

8

FORNUM

Verbatim response

Char

250

$TEXTVAR

1

Very satisfied

Num

8

TRASAT

2
3
4
.D
.R
.S

Satisfied
Dissatisfied
Very dissatisfied
Don't know
Refused
Appropriate skip

1
2
3
4
5
6
.D
.R
.S

Much shorter than expected
Shorter than expected
About what you expected
Longer than you expected
Much longer than you expected
You had no expectation
Don't know
Refused
Appropriate skip

Num

8

SCRETIME

.D
.R
.S
Most Recent Flight - Screening Wait - 5+ Hours Why

Length

_______ hours
Don't know
Refused
Appropriate skip

Most Recent Flight - Screening Wait - Decimal
Hours

T1060D

Type

.D
.R
.S
Most Recent Flight - Screening Wait - Minutes

T1060

Response Category Description

Text

Don't know
Refused
Appropriate skip

PAGE • 57

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

Type

Length

Format

T1090

T1090

Most Recent Flight - Screening - Time - Satisfaction

1
2
3
4
.D
.R
.S

Very satisfied
Satisfied
Dissatisfied
Very dissatisfied
Don't know
Refused
Appropriate skip

Num

8

TRASAT

T1100

T1100

Most Recent Flight - Additional Screening

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1110

T1110

Most Recent Flight - Screening - Intensity

1
2
3
.D
.R
.S

Excessive
Appropriate
Inadequate
Don't know
Refused
Appropriate skip

Num

8

SCREINTE

T1120

T1120

Most Recent Flight - Screening - Courtesy
Satisfaction

1

Very satisfied

Num

8

TRASAT

2
3
4
.D
.R
.S

Satisfied
Dissatisfied
Very dissatisfied
Don't know
Refused
Appropriate skip

1

Very well informed

Num

8

SCREINFO

2
3
4
.D

Moderately well informed
Slightly informed
Not at all informed
Don't know

T1130

T1130

Security Screening Procedures - Level of
Information

PAGE • 58

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

.R
.S

Refused
Appropriate skip

Type

Length

Format

T1140

T1140A

Screening Information - TSA Website

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1140

T1140B

Screening Information - Travel Experience

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1140

T1140C

Screening Information - Airline / Travel Agent
Website

1

Yes

Num

8

YESNO

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

1

Yes

Num

8

YESNO

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

1

Yes

Num

8

YESNO

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

1

Yes

Num

8

YESNO

T1140

T1140

T1140

T1140D

T1140E

T1140F

Screening Information - Called / Emailed to the
Airline

Screening Information - Called / Emailed to the
Travel Agent

Screening Information - Printed Material

PAGE • 59

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

Type

Length

Format

T1140

T1140G

Screening Information - Signs Displayed at Airport

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1140

T1140H

Screening Information - Radio, TV, Newspaper

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1140

T1140I

Screening Information - Friends, Family, Word of
Mouth

1

Yes

Num

8

YESNO

2
.D
.R
.S

No
Don't know
Refused
Appropriate skip

1
2
.D
.R
.S

Yes
No
Don't know
Refused
Appropriate skip

Num

8

YESNO

T1140

T1140J

Screening Information - Other

T1140

T1140K

Screening Information - Specified Other Source

Text

Verbatim response

Char

250

$TEXTVAR

T1150

T1150

Screening Information - Comment

Text

Verbatim response

Char

250

$TEXTVAR

T1160

T1160

Security - Flight Crew - Confidence

1
2
3

No confidence
A small amount of confidence
A moderate amount of confidence

Num

8

SCRECONF

PAGE • 60

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

4
5
.D
.R

A great deal of confidence
Total confidence
Don't know
Refused

Type

Length

Format

T1170

T1170

Security - Screening - Confidence

1
2
3
4
5
.D
.R

No confidence
A small amount of confidence
A moderate amount of confidence
A great deal of confidence
Total confidence
Don't know
Refused

Num

8

SCRECONF

T1180

T1180

Use of Cell Phones During Flight

1
2
3
4
5
.D
.R

Definitely should
Probably should
Not sure
Probably should not
Definitely should not
Don't know
Refused

Num

8

CELLPHON

D1010

D1010

Nb of Vehicles Used

_______ vehicles
Don't know
Refused

Num

8

FORNUM

.D
.R
D1020

D1020

Difficulty Traveling

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1040

D1040D

Birthday - Age Category - All Respondents

1
2
3
4
5
6

18 to 24 years
25 to 34
35 to 44
45 to 54
55 to 64
65 to 74

Num

8

AGE

PAGE • 61

Question
Code

Variable
Name

Variable Label

Response
Category

Response Category Description

7
.D
.R

75 or older
Don't know
Refused

Type

Length

Format

D1050

D1050

Gender

1
2
.D
.R

Male
Female
Don't know
Refused

Num

8

GENDER

D1060

D1060

Hispanic or Latino

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1070

D1070A

Race - White

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1070

D1070B

Race - Black

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1070

D1070C

Race - American-Indian, Aleut or Eskimo

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1070

D1070D

Race - Asian or Pacific Islander

1
2
.D
.R

Yes
No
Don't know
Refused

Num

8

YESNO

D1070

D1070E

Race - Other

1
2

Yes
No

Num

8

YESNO

PAGE • 62

Question
Code

Variable
Name

Variable Label

Response
Category
.D
.R

D1070

D1070F

Race - Other - Text

D1080

D1080

Education Level

Text
1
2
3
4
5

Response Category Description

Type

Length

Format

Verbatim response

Char

250

$TEXTVAR

Less than high school graduate
High school graduate (or GED)

Num

8

EDUC

Don't know
Refused

Some college (or technical vocational
school/professional business school)
Two-year college degree (AA: Associate in
Arts)
Four-year college degree (BA or BS: Bachelor
of Arts/Science degree)

6

Graduate degree (Master's, Ph.D., Lawyer,
Medical Doctor)

.D
.R

Don't know
Refused

D1090

D1090

HH Income

1
2
3
4
5
6
7
.D
.R

Under $15,000
From $15,000 to less than $30,000
From $30,000 to less than $50,000
From $50,000 to less than $75,000
From $75,000 to less than $100,000
From $100,000 to less than $125,000
$125,000 or more
Don't know
Refused

Num

8

INCOME

D1160

D1160

Nb of Home Telephone Numbers

1
2
3
4
.D
.R

One
Two
Three
Four or more
Don't know
Refused

Num

8

TOTPHON

D1170

D1170

Nb of Home Telephone Numbers - Confirmed

1
2

Yes
No

Num

8

YESNO

PAGE • 63

Question
Code

D1190

Variable
Name

Variable Label

D1190

Advance Notice

BASEWGT
NR_FACT
PER_FACT
PHN_FACT
CEN_FACT
WD_FACT
FNLWGT

Base Weight
Nonresponse Adjustment Factor
Adjustment for Nb of Eligible HH Members
Multiple Phone Lines Adjustment Factor
Census Population Adjustment Factor
Weighted Deflation Adjustment Factor
Final Weight

Response
Category

Response Category Description

.D
.R
.S

Don't know
Refused
Appropriate skip

1
2
3
.D
.R

Yes
No
Not sure
Don't know
Refused

PAGE • 64

Type

Length

Format

Num

8

PRECONT

Num
Num
Num
Num
Num
Num
Num

8
8
8
8
8
8
8

FORNUM
FORNUM
FORNUM
FORNUM
FORNUM
FORNUM
FORNUM

APPENDIX C: SAS FORMATS LIBRARY
PROC FORMAT cntlout=fmtout;
value msainout
1='MSA area'
2='Non-MSA area';
value censreg
1='Northeast'
2='Midwest'
3='South'
4='West';
value censdiv
1='New England'
2='Middle Atlantic'
3='East North Central'
4='West North Central'
5='South Atlantic'
6='East South Central'
7='West South Central'
8='Mountain'
9='Pacific';
value fornum
.d='Do not know'
.r='Refused'
.s='Skip';
value yesno
1='Yes'
2='No'
.d='Do not know'
.r='Refused'
.s='Skip';
value gender
1='Male'
2='Female'
.d='Do not know'
.r='Refused'
.s='Skip';
value traffica
1='Very congested'
2='Moderately congested'
3='Slightly congested'
4='Not at all congested'
.d='Do not know'
.r='Refused'
.s='Skip';
value trafficb
1='Much better'
PAGE • 65

2='Somewhat better'
3='Stayed about the same'
4='Somewhat worse'
5='Much worse'
.d='Do not know'
.r='Refused'
.s='Skip';
value homey
1='Convenience '
2='Saves the company money'
3='Saves me money'
4='Saves me time'
5='To avoid congestion'
6='Allows me to take care of family members or be home when kids
come home'
7='I do not live in the same area as the company I work for'
8='I work for multiple businesses'
9='I get more work done at home'
10='For health reasons or disability reasons'
11='Lack of transportation'
12='Any other reason'
.d='Do not know'
.r='Refused'
.s='Skip';
value triptime
1='Enter month and year'
2='Less than three months ago'
3='More than three months ago but less than one year ago'
6='One year ago'
4='More than one year ago'
.d='Do not know'
.r='Refused'
.s='Skip';
value trasat
1='Very satisfied'
2='Satisfied'
3='Dissatisfied'
4='Very dissatisfied'
.d='Do not know'
.r='Refused'
.s='Skip';
value scretime
1='Much shorter than expected'
2='Shorter than expected'
3='About what you expected'
4='Longer than you expected'
5='Much longer than you expected'
6='You had no expectation'
.d='Do not know'
.r='Refused'
.s='Skip';
value screinte
PAGE • 66

1='Excessive'
2='Appropriate'
3='Inadequate'
.d='Do not know'
.r='Refused'
.s='Skip';
value screinfo
1='Very well informed'
2='Moderately well informed'
3='Slightly informed'
4='Not at all informed'
.d='Do not know'
.r='Refused'
.s='Skip';
value screconf
1='No confidence'
2='A small amount of confidence'
3='A moderate amount of confidence'
4='A great deal of confidence '
5='Total confidence'
.d='Do not know'
.r='Refused';
value cellphon
1='Definitely should'
2='Probably should'
3='Not sure'
4='Probably should not'
5='Definitely should not'
.d='Do not know'
.r='Refused';
value age
1='18 to 24 years'
2='25 to 34'
3='35 to 44'
4='45 to 54'
5='55 to 64'
6='65 to 74'
7='75 or older'
.d='Do not know'
.r='Refused'
.s='Skip';
value educ
1='Less than high school graduate'
2='High school graduate (or GED)'
3='Some college (or technical vocational school/professional
business school)'
4='Two-year college degree (AA: Associate in Arts)'
5='Four-year college degree (BA or BS: Bachelor of Arts/Science
degree)'
6='Graduate degree (Masters, Ph.D., Lawyer, Medical Doctor)'
.d='Do not know'
.r='Refused';
PAGE • 67

value income
1='Under $15,000'
2='From $15,000 to less than $30,000'
3='From $30,000 to less than $50,000'
4='From $50,000 to less than $75,000'
5='From $75,000 to less than $100,000'
6='From $100,000 to less than $125,000'
7='$125,000 or more'
.d='Do not know'
.r='Refused';
value totphon
1='One'
2='Two'
3='Three'
4='Four or more'
.d='Do not know'
.r='Refused';
value precont
1='Yes'
2='No'
3='Not sure'
.d='Do not know'
.r='Refused';
RUN;

PAGE • 68

REFERENCES
Books:
"Sampling of Populations: Methods and Applications," 3rd Ed., 1999, Paul S. Levy (School of
Public Health, University of Illinois at Chicago) and Stanley Lemeshow (School of Public
Health, University of Massachusetts)
"Practical Methods for Design and Analysis of Complex Surveys," 1995, Risto Lehtonen (The
Social Insurance Institution, Finland) and Erkki J. Pahkinen (University of Jyvaskyla)
"Sampling Techniques," 2nd Ed, 1967, William G. Cochran (Harvard University), Wiley
"SUDAAN Release 7.5, User's Manual Volume I and II," 1997, Babubhai V. Shah, Beth G.
Barnwell and Gayle S. Bieler, Research Triangle Institute

Articles:
"1999 Variance Estimation," National Survey of America's Families Methodology Report, 1999
Methodology Series, Report No. 4, prepared by J.M. Brick, P. Broene, D. Ferraro, T. Hankins, C.
Rauch and T. Strickler, November 2000
"Pitfalls of Using Standard Statistical Software Packages for Sample Survey Data," Donna J.
Brogan, Encyclopedia of Biostatistics, edited by P. Armitage and T. Colton, John Wiley, 1998
"Sampling and Weighting in the National Assessment", K. Rust and E. Johnson, Journal of
Educational Statistics, 17(2): 111-129, 1992
"Poststratification and weighting adjustments," Andrew Gelman and John B. Carlin, Department
of Statistics, Columbia University Working Paper, February 2000
"Sampling Variances for Surveys With Weighting, Poststratification, and Raking," Hao Lu and
Andrew Gelman, Department of Statistics, Columbia University Working Paper, April 2000

PAGE • 69