30601128
March 2010
B. Collections of Information Employing Statistical Methods:
The agency should be prepared to justify its decision not to use statistical methods in any case where such methods might reduce burden or improve accuracy of results. When item 17 on the Form OMB 83I is checked, "Yes," the following documentation should be included in the Supporting Statement to the extent that it applies to the methods proposed:
1. Describe (including a numerical estimate) the potential respondent universe and any sampling or other respondent selection methods to be used. Data on the number of entities (e.g., establishments, State and local government units, households, or persons)in the universe covered by the collection and in the corresponding sample are to be provided in tabular form for the universe as a whole and for each of the strata in the proposed sample. Indicate expected response rates for the collection as a whole. If the collection had been conducted previously, include the actual response rate achieved during the last collection.
The target population for this study is the adult population of the 50 states of the United States.
The study will focus on both on households estimated to total 129,065,264 as of July 1, 2008, as well as individuals. The survey will seek reliable national estimates for the internet broadband penetration at the household level.
In addition, the survey will attempt to provide a reliable national estimate of the number of American adults who do not currently use or have access to a broadband internet connection in their household. The estimated civilian noninstitutional population age 18 and older as of 2008 is 224,703,000.
Based on recent experience, this survey, calling landline and cell phone numbers, will achieve an response rate of between 20 and 30 percent using the appropriate American Association of Public Opinion Research (AAPOR) response rate definitions. This response rate is solidly in the higher range of response rates based on telephone surveys with constrained interviewing periods.
2. Describe the procedures for the collection of information including:
Statistical methodology for stratification and sample selection,
Estimation procedure,
Degree of accuracy needed for the purpose described in the justification,
Unusual problems requiring specialized sampling procedures, and
Any use of periodic (less frequent than annual) data collection cycles to reduce burden.
As directed by the FCC, the survey is designed to achieve appropriate national estimates of population parameters of plus or minus 2 percentage points at a 95 confidence level.
The consumer survey will be conducted using one questionnaire but using different screening efforts to maximize the number of nonbroadband adopters available for analysis.
The initial portion of the survey, designed to provide rigorous estimates of broadband characteristics of all American households at the national level, will consist of 4,000 completed interviews with adults age 18 and older in the 50 states and the District of Columbia. This design should provide roughly 2,400 interviews with broadband adopters, 1,500 with nonadopters, and the remainder whose status could not be determined. This portion of the survey will provide national estimates of broadband adoption and nonadoption subject to sampling errors of no more than plus or minus 2 percentage points at the 95 percent confidence level.
Once the 4,000 completes are achieved, the screening will begin. The CATI system will route adopters to the demographic questions only. Then 1,000 additional full interviews will be done with nonadopters, bringing the total number of nonadopters approximately 2,500. In addition, the survey will collect demographic information on those adults who are not nonadopters (the failed screeners in the survey consisting of broadband adopters and others of indeterminate status) adding broadband status and demographic data on an additional 1,800 adults.
National Consumer Survey 


Total full interviews 
Interviews with: 

Broadband adopters 
Non adopters 
Other 

Main survey 
4,000 
2400+/ 
1500 +/ 
100+/ 
Nonadopters survey 
1,000 
0 
1,000 
0 
Total interviews 
5,000 
2,400+/ 
2,500+/ 
100+/ 

Screenout interviews 

From nonadopters survey 
1,800 
1,700+/ 
0 
100+/ 
One should note that this design provides the requested level of accuracy for the total main survey. Estimates of the characteristics and behaviors of sub groups – including adopters as one subgroup and nonadopters as another subgroup – will be subject to higher sampling error margins based strictly on the smaller number of interviews in a specific subgroup.
The second segmentation of the population that is critical to this study is the UrbanSuburbanRural (U/S/R) continuum. The basic classification of the data will be based on an analysis of the location of the telephone exchange of the landline telephone number. The classification is subject to a certain degree of error, especially since the definition of suburban is not widely accepted. However, for cell phone numbers the U/S/R determination is much harder since the location reported to the telephone sample provider is related to where the cell phone was activated which may or may not have relevance to current home address for the respondent. Using techniques developed by PSRAI, each cell phone interview will be categorized in terms of U/S/R/.
The average expected length of the interview for adopters and for nonadopters in the main survey will be no more than 20 minutes. The length of interview for nonadopters in the second survey should also last no more than 20 minutes on average. The average interview length for the screenouts in this second survey (most adopters) should be no more than 7 minutes.
The survey will be conducted in English or Spanish, at the respondent’s discretion.
The survey will be conducted using two samples:
A standard Random Digit Dialing (RDD) sample of landline telephones; and
An RDD sample of cell phones.
Consumer telephone Samples
Two
samples will be used for the consumer data collection  a random
digit dial (RDD) landline sample and an RDD cell sample. The landline
sample frame will be an equal probability sample across all active
blocks.^{ 1}
All blocks within a county will be sorted in ascending order by area
code, exchange and block number. A sampling interval will be computed
for each county in our sample by summing all eligible blocks in the
county and dividing that sum by the quota assigned to the county.
From a random start between zero and the sampling interval, blocks
are systematically selected from each county. Once a block has been
selected, a twodigit random number is appended to the block to
create a phone number. Business numbers will not be excluded at the
sampling stage. Rather we will purge the numbers flagged as business
before the numbers are dialed.^{2}
Additionally, we will not exclude protected numbers from our sample.^{3}
The cellular sample will not be listassisted because no list of cellular numbers exists. Rather, cellular phone numbers will be systematically sampled from dedicated wireless 100blocks and shared service 100blocks with no directorylisted landline numbers.
Sample Weighting
The
landline and cell samples will be combined in analysis. The data will
be weighted to correct for three sample elements that could bias
sample estimates  [1] the oversampling through screening of
nonadopters, [2] different probabilities of selection based on phone
use and, [3] disproportionate nonresponse.
Nonadopters Oversample: As mentioned above, in order to increase the number of nonadopters in our final sample data collection will happen in two phases. The first phase of will include interviewing with 4,000 adults in the 50 states and the district and the second phase will comprise interviews with an additional 1,000 nonadopters. Therefore, nonadopters will be overrepresented in our final sample. The first stage of weighting will adjust all nonadopters down so that the proportion in our total sample equals the proportion from phase one interviewing. For example, we project that phase one interviewing will include 1,500 nonadopters. Phase two interviewing will bring the total pool of nonadopters up to 2,500 nonadopters. These 2,500 nonadopters will be given a weight adjustment of 1,500/2,500 = 0.60 to bring them down to their proper proportion.
Different Probabilities of Selection based on Phone Use: The people and households we interview will have different probabilities of being in our sample based on three variables: [a] the number of phone lines in the household; [b] the number of adults in the household; and [c] the number of adults in the household who have a cell phone. For example, a person who lives alone in a house with one landline phone will have twice the probability of being in our landline sample as an adult who lives with one other adult in a household with only one phone. Likewise, an adult with both a landline and a cell phone has twice the probability of being sampled as an adult with only one kind of phone.^{4}
The probability of a household being included in the sample is a function of the number of phone lines into the household (n_{L}) and the number of adults with cell phones (n_{C}). We will assume independence in the sampling of the two frames so the probability that a household is sampled will be the probability it is sampled by landline plus the probability it is sampled by cell (P_{L}n_{L} + P_{C}n_{C}). Then the appropriate weighting adjustment to correct for unequal probabilities of household selection would be 1/(P_{L}n_{L} + P_{C}n_{C}). If we assume that P_{L }= P_{C} = P, then the probability of a household being selected would simplify to P(n_{L} + n_{C}) and the adjustment would simplify to 1/(n_{L}+n_{C}).
The probability that a person will be sampled will be a function of the number of phone lines in the household, the number of adults in the household (n_{A}) and whether or not the person has a cell phone. So the probability of being sampled would be:
P_{L}n_{L}/n_{A} + P_{C} if the person has a cell phone, or
P_{L}n_{L}/n_{A }if the person has no cell phone (i.e., P_{C}=0)
If we again assume that P_{L} = P_{C} = P, then the probabilities simplify to:
P×n_{L}/n_{A} + P = P×(n_{L}/n_{A} + 1) = P×(n_{L}+n_{A})/n_{A} if the person has a cell phone
P×n_{L}/n_{A} if the person has no cell phone
So the proper adjustment to make the probabilities of selection constant would be:
n_{A}/(n_{L}+n_{A}) if the person has a cell phone, or
n_{A}/n_{L }if the person has no cell phone
Differential nonresponse: It is well established (at least in landline samples) that certain kinds of people are easier to reach and more cooperative than others and therefore end up overrepresented in RDD samples. One example of this is that older people are much easier to reach by landline phone and are almost always overrepresented in landline samples. In order to correct for this kind of potential bias in our sample we will rake the final sample demographics to match population parameters. We will rake the data to match population parameters for: sex by age; sex by education; age by education; race/ethnicity; census region; population density and telephone use. All but two of the parameters will be derived from the Census Bureaus’ 2009 ASEC data. The population density parameter will come from an analysis of Census 2000 data at the county level. The phone use parameter will come from the most recently available statistics from the National Health Interview Survey. ^{5}
Effect of Weighing on Sample Estimates
Postdata collection statistical adjustments require
analysis procedures that reflect departures from simple random
sampling. PSRAI calculates the effects of these design features so
that an appropriate adjustment can be incorporated into tests of
statistical significance when using these data. The socalled "design
effect" or deff represents the loss in statistical
efficiency that results from disproportionate sampling and systematic
nonresponse.
PSRAI calculates the composite design effect for a sample of size n, with each case having a weight, wi as:
formula 1
In a wide range of situations, the adjusted standard error of a statistic should be calculated by multiplying the usual formula by the square root of the design effect (√deff ). Thus, the formula for computing the 95% confidence interval around a percentage is:
formula 2
where is the sample estimate and n is the unweighted number of sample cases in the group being considered.
We estimate that the total sample design effect will be between 1.30 and 1.50 and that the final total sample margin of error will range from 1.6 to 1.7 percentage points.
3. Describe methods to maximize response rates and to deal with issues of nonresponse. The accuracy and reliability of information collected must be shown to be adequate for intended uses. For collections based on sampling, a special justification must be provided for any collection that will not yield "reliable" data that can be generalized to the universe studied.
The survey will be conducted in accordance with best practices of the survey industry. Trained and experienced interviewers will be briefed on the project, its goals and the specifics of the questionnaire. A full 15call design will be implemented for the landline survey with a 7call design for the cell phone numbers. This means that the field house will make up to 15 calls to each landline telephone number in the sample in an effort to complete an interview. Recent PSRAI experience suggests that calling cell phone numbers repeatedly in an attempt to complete an interview beyond 7 calls is not productive. A telephone number will be removed from the active sample only when a terminal disposition has been achieved for that number (completed interview, nonworking number, business number, hard refusal, etc.) Refusal conversion will be attempted at least once on all soft refusals.
Plan to Examine Potential NonResponse bias
In order to quantify and measure potential nonresponse bias on survey results, we propose investigating two types of nonresponse. First, we will look at unit nonresponse. This is nonresponse at the survey level caused by not contacting potential respondents or not gaining cooperation once a potential respondent is reached. We will also investigate item nonresponse. This is nonresponse at the questionlevel and is caused by people not answering specific questions during the interview.
Unit nonresponse
The first step in our unit nonresponse analysis will be to use an approach, in line with Keeter, et. al. and previous PSRAI analyses, that will segment the completed interviews by the level of effort that was required to get the interview.
We will segment the completed interviews into four categories based on the amount of “effort” it took to complete the interview. “Effort” will be measured as a function of the number of calls and refusal conversions necessary to gain cooperation.
We will start with the following definitions that we have used in a past nonresponse analysis, but which may be modified slightly.
Least effort. Five or fewer calls and no refusal conversions.
Five or fewer calls with one refusal conversion or six to ten calls with no refusal conversions.
Six to ten calls with at least one refusal conversion.
Most effort. More than ten calls.
We will also experiment with second way to measure effort which will simply be to assign an effort measure E to each completed interview defined as E = C + R, where C is the number of calls made and R is the number of refusals. For example, if a number was called three times with one refusal, then E=3+1=4.
These effort measures will then be used to compare and contrast key survey results. For example, we will see if the harder to reach respondents are more or less likely to have broadband access in their home.
Where population parameters are available, we will see what effect extra effort has on the quality of our data. For example, from Census data we know the demographic profile of the adult population (e.g., sex, age, education, and race/ethnicity). We will be able to see what effect more effort has in matching sample demographics to population parameters.
This effort will draw on the 2007 work done by PSRAI. As part of a project for the University of Illinois and the Pew Internet and American Life Project that was funded by the Institute for Museum and Library Studies,^{6} a study of possible nonresponse bias in a large national telephone survey was conducted at the request of OMB. A version of the analysis is available online.^{7}
A benchmarking step
In addition, PSRAI will conduct an analysis of how the results of the survey compare with the October 2009 Supplement on Internet and Computer Use to the Current Population Survey, when that data is available. PSRAI may not be able to obtain that data before the conclusion of this contract, but it will conduct the analysis.
Item nonresponse
Item nonresponse is due to respondents no answering specific questions during the interview. We will investigate unit nonresponse by identifying which questions have the highest and lowest levels on “DK/Ref” response. We will compare item results with item nonresponders both included and excluded and see what effect this has on reported results. We will also compare item nonresponse for the two sample frames. We will identify questions that have different levels of nonresponse by sample frame.
We can also see if there is a link between item and unit nonresponse. We will investigate whether people who are harder to reach have different levels of item nonresponse than those who are easier to reach. This analysis will involve comparing levels of item nonresponse across different kinds of respondents we identify in the unit nonresponse analysis.
4. Describe any tests of procedures or methods to be undertaken. Testing is encouraged as an effective means of refining collections of information to minimize burden and improve utility. Tests must be approved if they call for answers to identical questions from 10 or more respondents. A proposed test or set of test may be submitted for approval separately or in combination with the main collection of information.
A field test will be held to confirm the questionnaire design, question wording and CATI programming of the surveys.
If the field test is held after OMB approval has been provided, the survey will be field tested in the following manner:
The questionnaire will be programmed in the CATI system and the programming checked for accuracy.
A small group of interviewers will be briefed on the study.
These interviews will then complete up to 50 interviews with actual respondents from the appropriate populations.
The interviews will be closely monitored by field house supervisors and debriefed at the end of each shift.
A focus will be on question clarity and assuring that the respondent understands each question.
In addition, the flow of the questionnaire will be judged, based on how respondents deal with changes in topics throughout the survey.
The interviewers will be checked for proper performance and adherence to the survey instructions.
The proper functioning of the CATI system will be checked in real time and the appropriate log files examined for any problems.
Should the field test take place in advance of OMB approval, the field house will conduct the field test using its employees as test respondents. Other than field house staff, the only other individuals who may be contacted for the field test are staff members of PSRAI or the FCC. Other than the change in source of the respondents and a reduction in the total number of interviews, the test will proceed as if members of the public were being interviewed.
PSRAI will prepare a short report on the field tests for the FCC.
5. Provide the name and telephone number of individuals consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.
John B. Horrigan, PhD
Consumer Research Director
National Broadband Task Force
2024181553 (office)
4439042709 (cell)
1 Active blocks are defined as 100 contiguous phone numbers (e.g., 6099249200 to 6099249299) with at least one residential directory listing.
2 The reason we do not have SSI purge the business numbers is that their sampling program automatically replaces a purges business number with another RDD number from the same block. This will, in effect, oversample numbers in blocks with business numbers.
3 Phone numbers in SSI random digit database are flagged as “protected” if they have recently been pulled for any sample order. While excluding protected numbers will resulting in a “fresher” sample (i.e., one that consists of numbers that have not been recently pulled), we feel that excluding these numbers could potentially bias our sample.
4 We will assume that the probability of being sampled in each frame is equal.
5 Blumberg SJ, Luke JV. Wireless substitution: Early release of estimates from the National Health Interview Survey, JulyDecember, 2008. National Center for Health Statistics. May 2009.
6 IMLS grant award number LG0605039805, OMB Clearance Number, 31370070, expiration date 06.30.2010.
7 How Different Are People Who Don’t Respond to Pollsters?,Witt and Best, April 21, 2008, pewresearch.org/pubs/807/howdifferentarepeoplewhodontrespondtopollsters
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