06/22/13 Page 1

PART B: COLLECTION OF INFORMATION EMPLOYING STATISTICAL METHODS

Part B applies to four WaterSense data collection efforts: a census survey of all organizational 

partners, a census survey of all licensed certification providers, and two consumer surveys, one 

of which uses sampling techniques. Section I describes the required elements for the annual 

reporting process for all organizational partners and quarterly reporting for all licensed 

certification providers, Section II discusses these elements for the consumer awareness phone 

survey, and Section III discusses these elements for the Internet-based consumer survey.

SECTION I: ANNUAL REPORTING CENSUS AND QUARTERLY LICENSED 

CERTIFICATION PROVIDER CENSUS

B1. Describe (including a numerical estimate) the potential respondent universe and any 

sampling or other respondent selection method to be used. Data on the number of 

entities (e.g., establishments, state and local government units, households, 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 rate for the collection as a whole. If the 

collection has been conducted previously, include the actual response rate achieved 

during the last collection.

WaterSense will collect data from promotional partners, manufacturers, 

retailers/distributors, and builders via annual reporting each year from 2013 to 2016. WaterSense 

plans to collect data from professional certifying organizations from 2014 to 2016. WaterSense 

will collect data from all providers on a quarterly basis. 

As of February 2013, WaterSense has 1,372 reporting partners. This is a census survey,

and no sampling methods will be used for either the annual or quarterly surveys. Table B-1 

summarizes the number of partners by type.

B-1: WaterSense Reporting Partners by Partner Type, February 2013

Partner Type Number

Promotional 829

Manufacturer 239

Retailers/Distributor 206

Builder 66

Professional Certifying 

Organization 14

Licensed Certification 

Providers 18

Total 1,372
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Table B-2 summarizes the actual response rate received for the annual census during 

previous data collections. 

B-2: WaterSense Annual Reporting by Partner Type, 2009-2011*

Partner Type Reporting Year Response Rate

Promotional 2011 30 %

2010 33 %

2009 52 %

Manufacturer 2011 36 %

2010 44 %

2009 41%

Retailer/Distributor 2011 10 %

2010 12 %

2009 20%

Builder 2011 7 %

2010 28 %

2009 N/A – reporting not required

Professional Certifying 

Organization

2009-2011 N/A – reporting not required

*Response rates for previous years available upon request. 

B-3: WaterSense Quarterly Reporting for Licensed Certification Providers, 2010-2011 

Partner Type Reporting Quarter Response Rate

Licensed Certification 

Providers

Q3 2012 53 %

Q2 2012 47 %

Q1 2012 40 %

Q4 2011 53 %

Q3 2011 40 %

Q2 2011 31 %

Q1 2011 55 %

Q4 2010 64 %

B2. Describe the procedures for the collection of information including: (a) statistical 

methodology for stratification and sample selection; (b) estimation procedures; (c) 

degree of accuracy needed for the purpose described in the justification; (d) unusual 

problems requiring specialized sampling procedures; and (e) any use of periodic 

(e.g., less frequent than annual) data collection cycles to reduce burden.

Annual Reporting 

All WaterSense partners except for irrigation partners and licensed certification providers

(who submit quarterly reports as discussed below) submit an annual reporting form electronically 

via an online form. In addition, manufacturer and retailer/distributor partners are also required to 

submit shipment and sales data to a WaterSense contractor. The data will be recorded on annual 
06/22/13 Page 3

reporting forms and received via the U.S. mail or private delivery service. EPA anticipates that 

most, if not all, partners will request that shipment and sales data be handled as CBI. WaterSense 

procedures assume that all shipment and sales data will be handled as CBI. Upon receipt of an 

annual reporting form with shipment data, the WaterSense data manager provides a listing of 

reporting partners to the WaterSense Helpline staff. Helpline staff verify eligibility of the partner 

to report by checking the listing of partners in the manufacturer category. If the partner is not 

eligible to report, Helpline staff contact the partner to discuss their partnership category and 

revise the partner’s designation in Salesforce, if necessary, or inform the data manager and the 

Helpline manager that the partner incorrectly submitted data. If the partner is not eligible to 

report, the data manager will not include the partner’s data in subsequent analyses and note the 

decision on the partner’s reporting form. After confirming eligibility to submit data, the data 

manager or her designee, will review each submission to determine:

 Does the manufacturer own the original certification file? This step reduces the chances 

of double counting shipment data submitted by the original manufacturer and others who 

rebrand and resell the products.

 Are there internal inconsistencies in the report (e.g., number of WaterSense products 

shipped exceeds the total number of products shipped)?

 Are the data unrealistic for the given partner (e.g., shipments are excessive for what 

might be expected for a company of size reporting)?

 Is there evidence that the partner has provided estimated data rather than actual? 

 Is there evidence that the partner has included international shipments or sales?

If the answer to any of the above questions is yes, ERG will contact the partner to clarify. If the 

partner cannot sufficiently explain the data, they will not be included in subsequent data 

analyses.

Provider Reporting

Licensed certification provider partners submit quarterly reporting forms electronically 

via an online form. WaterSense receives these online forms from partners four times a year, in 

early February, May, August, and November. The reporting form asks for contact information as 

well as information about the WaterSense labeled new homes that the provider organization 

inspected during the previous calendar quarter.

Upon receipt of a quarterly reporting form, Helpline staff verifies that the partner is a 

bona fide “provider” partner and that contact information for the primary contact at the 

organization has not changed, and, if it has, updates the WaterSense database accordingly. After 

confirming eligibility, Helpline staff marks the year and quarter (i.e., Q1 2012) that the 

information should be associated with in the database. The Helpline manager reviews each 

submission for reasonableness (e.g., has there been a large increase or decrease in figures 

reported in previous reports; does the reported figure seem reasonable given the size of the 

organization and timeframe of the report), and follows up with the partner to clarify any 

questions about the data submitted. The Helpline manager then sends an email to any builder 

partners who are referenced in the quarterly reports to verify that the new homes information 

submitted was accurate.
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B3. Describe methods to maximize response rates and to deal with issues of nonresponse. The accuracy and reliability of information must be shown to be adequate 

for intended use. 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.

Upon joining WaterSense, EPA requires organizational partners to commit to submitting 

annual reports and requires provider partners to submit quarterly reports. The importance of both 

annual reporting processes is stressed to partners upon joining. To maximize response EPA 

conducts the following activities:

 Require the submission of an annual reporting form for those partners wishing to be 

considered for a WaterSense award.

 Host a partner conference call to answer partner questions about the form.

 Send emails to remind partners of upcoming due dates.

 Remind partners about reporting in quarterly newsletter.

 Follow-up phone calls to non-reporting partners.

 Send 1-2 reporting reminder emails to provider partners each quarter.

B4. 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 tests may 

be submitted for approval separately or in combination with the main collection of 

data.

EPA provided draft versions of the annual reporting form and quarterly reporting form to 

several partners (fewer than 10) for comment and revised the form accordingly. Upon the 

completion of each data collection cycle, EPA examines the responses, form, and procedures and 

identifies potential changes for the following year based on common questions or issues that 

arise.

B5. 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 collect and/or analyze the information for the agency.

Laura Harwood of Eastern Research Group, Inc. (ERG) is the task manager for both the 

census surveys and can be reached at (703) 841-0589. Roy Sieber serves as ERG’s program 

manager and can be reached at (703) 633-1614. Dr. Lou Nadeau is an ERG senior economist and 

can be reached at (781) 674-7316. 
06/22/13 Page 5

SECTION II: CONSUMER AWARENESS PHONE SURVEY

B.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, 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 these two surveys will be households in the United States. This 

corresponds to the target population of the WaterSense program. The sampling population will 

be adults living in households that are surveyed. There are 115 million households in the United 

States according to the most recently available Census Bureau numbers.1From this, EPA will 

select a sample of 400 respondents for each survey. The justification for this sample size appears 

in response to Question B.2 below. The sampling frame will be a list provided by a telephone 

survey contractor. Lists of U.S. households are readily available for this type of survey. 

EPA has not previously conducted these surveys, thus it cannot estimate the expected 

response based on past experience. Evaluation practitioners have documented that survey

response rates have been declining worldwide in recent years.2In a recent study3of response 

rates for 205 telephone surveys conducted in the same survey lab over a three-year period, study

authors found that response rates varied from fewer than 10 percent to greater than 90 percent 

response, with the largest number of surveys falling in the 25 to 45 percent range. Further, the 

study authors found that response rates are affected by contextual variables including:

 Salience of the survey to the population

 Survey length

 Type of sample (e.g., listed versus random-digit dialing)

 Minutes per piece of sample (i.e., effort)

 Amount of time the survey was in the field 

A 10-minute increase in survey length results in a 7 percent decrease in the response rate. Since 

the proposed WaterSense customer awareness survey is short, EPA anticipates a relatively high 

response rate. In addition, EPA will take actions to maximize response rate (see discussion in 

Section B.3 below). Given these factors, EPA estimates a response rate of approximately 40 

percent for the consumer awareness survey. 

 

1

http://factfinder2.census.gov/bkmk/table/1.0/en/ACS/11_1YR/DP02.

2

See de Leeuw, Edith, and Wim de Heer. 2002. “Trends in Household Survey Nonresponse: A Longitudinal and 

International Comparison.” In Survey Nonresponse, ed. Robert M. Groves, Don A. Dillman, John L. Eltinge, and 

Roderick J. A. Little, pp. 41–54. New York: Wiley; Singer, Eleanor. 2006. “Introduction— Nonresponse bias in 

household surveys.” Public Opinion Quarterly, 70(5):637-645. DOI:10.1093/poq/nfl034. 

3 McCarty, C., M. House, et al. (2006). “Effort in Phone Survey Response Rates: The Effects of Vendor and ClientControlled Factors.” Field Methods 18(2): 172-188.
06/22/13 Page 6

B.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

• Any use of periodic (e.g., less frequent than annual) data collection cycles to 

reduce burden.

Statistical Method for Stratification and Sample Selection

This section discusses the statistical methods for stratification and sample selection used 

in the survey. Before discussing those methods, the section begins by explaining EPA’s approach 

to estimating the sample size for this collection.

Sample Size Estimation

This section provides estimates of sample size needed to meet a set of specific statistical 

criteria for the survey data. Choosing a sample size is a three-step process. First, statistical 

criteria are set; second, an initial sample size is chosen based on the criteria; and third, if 

necessary, the initial sample size is adjusted based on the population size. The third step, 

however, is not needed for this survey due to the large universe size. The section begins with a 

discussion of the statistical criteria and then discusses the estimated initial and adjusted sample 

sizes.

The statistical criteria used in choosing a sample size are:

 Precision: The maximum difference in the parameter of interest between an estimate 

for that parameter obtained from the sample and the value of that parameter in the 

population.

 Confidence: The probability of correctly accepting a true hypothesis.

 Power: The probability of correctly rejecting a false hypothesis.

Simultaneously setting values for each criterion will generate a sample size estimate. In 

general, however, there are limited acceptable choices in terms of power and confidence and, 

therefore, most of the emphasis is in choosing a reasonable precision. To select sample size using 

these criteria, EPA has used statistical power analysis techniques (Cohen, 1988). The use of each 

in choosing a sample size is discussed in what follows.

Precision

The precision of a sample is the maximum difference in units of the key question that one 

is willing be away from the population parameter of interest. The parameter of interest for this 

survey is awareness of the WaterSense program. There are two key aspects of this parameter:

 The level of awareness (i.e., what percentage of households are aware of the 

program?).

 Whether or not awareness is increasing over time (i.e., is there a statistically

significant increase in awareness between surveys?).
06/22/13 Page 7

The first reflects estimation of a proportion (e.g., percentage of households aware of the 

program) and the second reflects a change in a proportion over time. Thus, precision will need to 

be in terms of percentage points. EPA has determined that the sample size should provide valid 

data for the second aspect (i.e., change in awareness over time), but should also provide 

reasonable reliable data to determine the level awareness also. EPA has determined that the 

sample should be able to detect three to five point change in awareness over time.4For example, 

if awareness is found to be 5 percent in this survey and a subsequent survey finds awareness to 

be 10 percent, the sample sizes for each survey should be large enough to find that change to be 

statistically significant.

Power

The power of a statistical test is one minus the probability of a Type II error (e.g., not 

rejecting a false hypothesis), or the probability of correctly rejecting a false hypothesis. In this 

sense, power corresponds to finding the specified effect size (i.e., precision) when that effect in 

fact exists. Traditional hypothesis tests set, by default, power to 50 percent. Following Cohen’s 

(1988) suggestion, EPA will use 80 percent power. Thus, in terms of the second aspect identified 

above under precision (change in awareness over time), the sample size will have an 80 percent 

chance of detecting the specified change in awareness if that change actually occurred.

Confidence

Confidence is the probability of accepting a true hypothesis. For purposes of sampling, 

confidence defines the likelihood that the population mean will be contained in the interval 

around the sample mean defined by the precision for the sample. EPA will use 90 percent 

confidence in setting the sample size. Furthermore, since EPA is interested in increases in 

awareness, EPA will use a one-sided confidence interval.

Sample Size Estimates

The initial sample size estimates are based on the methods of Cohen (1988), Chapter 6, 

which provides power analytic methods for detecting differences between proportions over time. 

EPA combined these methods with the precision, power, and confidence setting discussed above 

and an assumption on the current level of awareness in the universe. Setting a sample size for 

proportions requires either having some knowledge of proportion for the population beforehand, 

or making an assumption on the proportion for the population. EPA expects that awareness of 

WaterSense is fairly low among the universe and has assumed it to be between two and ten 

percent. Thus, the sample size should be able to detect three to five percent increase in awareness 

(precision) between surveys from the assumed baseline levels of awareness at 90 percent 

confidence and 80 percent power. Table B-3 provides sample sizes needed to detect the increases 

in awareness for the assumed range of baseline awareness (for the set power and confidence). 

Based on this table, EPA has selected a sample size of 400 households. Sample sizes in the table 

that are less than 400 households are depicted in bold italics. As can be seen, a sample of 400 

 

4 EPA has specified a range for precision due to uncertainty over the baseline level of awareness. This will be 

discussed in more detail below under sample size estimation.
06/22/13 Page 8

households will allow for detection of a five point increase in awareness from all baseline levels, 

detection of a four point increase in awareness for baseline awareness in the two to five percent 

range of baseline awareness, and detection of a three point increase in awareness for very low 

baseline awareness (2 percent).

Table B-3. Sample Sizes Needed to Detect the Specified 

Precision Values for Assumed Values of Baseline Awareness 

Between Two and Ten Percent at 90 Percent Confidence and 

80 Percent Power

Assumed 

Baseline 

Level of 

Awareness in 

the Universe

Precision: Increase in Awareness to be 

Detected

Three 

Percentage 

Points

Four 

Percentage 

Points

Five 

Percentage 

Points

2% 323 203 143

3% 419 257 178

4% 512 310 212

5% 602 360 244

6% 689 409 275

7% 774 457 306

8% 857 503 335

9% 938 548 364

10% 1016 592 391

Note: The values in Table B-3 are calculated using the following 

formula:

 

n

n

p r p



 

0 1

2

100 2 2

.

arcsin arcsin

where n0.1 is equal to 902 (in this case) and is derived from Cohen, 

Chapter 6, table 6.4.1 (third panel) and reflects a base sample size 

for one-sided 90 percent confidence and 80 percent power, p are 

the baseline awareness values, and r are the precision values.

Sample Allocation

EPA will allocate the sample across the United States in proportion to the distribution of 

households in the United States.

Estimation Procedure

Estimation of population parameters (means, totals, and variances) will be done by 

appropriately weighting the sample values. The weight for any responding sample unit can be 

calculated as:
06/22/13 Page 9

weight = (weight associated with sampling)  (weight that adjusts for nonresponse)

Estimation of these weights are discussed below, followed by calculation of weighted estimates 

for the population parameters. 

The weights associated with sampling can be estimated as the reciprocal of the selection 

probabilities. These can be estimated as:

w

N

n

hj w

h

h

h   (6)

where Nh is the population for stratum h and nh is the sample chosen from the stratum h. The 

second equality indicates that the weight for each sample unit from a specific stratum will be the 

same as all of sampled units from that stratum.5

To account for nonresponse, EPA will use a weighting class adjustment procedure. 

Specifically, EPA assumes that the probability that any population unit responds to the survey is 

the product of the selection probability (above) and a response probability. To estimate response 

probabilities, EPA will divide the respondents in each survey into a small number of classes 

(strata). The exact classes for each survey will depend on the nature of the data available for each 

group. The response probabilities are then:

k

sum of weights for respondents in k

sum of weights for selected sample in k



( )

( )

(7)

where k indexes the nonresponse weighting classes. Thus, the weight for a respondent in class k

and stratum h becomes:

~w

N

n

hk

h

h k



1



(8)

The weighted total for any question in these surveys can be found using the following 

formula:6

 ~ Y w y hj hj

j

J

h

H h



 

 

1 1

(9)

where Y



is the weighted estimate of the population total for variable/question y, h indexes strata, 

H is the total number of strata used in the survey, j indexes sample respondents within each 

 

5 This will not be true once weighting for nonresponse is done.

6 A number of questions asked in the surveys can be thought of as yes/no questions (e.g., explicit yes/no questions as 

well as ‘check all that apply’ questions). The ‘totals’ from these will be the number that respond ‘yes’ to the 

question.
06/22/13 Page 10

stratum, Jh is the total number of respondents in stratum h, 

~whj is the nonresponse-adjusted 

sampling weight for the jth unit in stratum h,

7

and yhj is the value for the variable/question y for

the jth unit in stratum h. Estimates of the population means can then be found as:





~

Y

Y

whj

j

J

h

H h



 

 

1 1

(10)

Estimation of the variance for the expressions in equations (9) and (10) will require more 

complex methods. The variance of both expressions will need to account for (a) the fact that each 

represents a sample estimate of a population parameter and (b) the fact that the response weights 

defined in (7) are sample quantities (i.e., they are not fixed). To calculate these variances, EPA

will use a bootstrap method. Bootstrap methods involve repeated sub-sampling (with 

replacement) of the selected sample and calculating the variance from the repeated samples. In 

theory, if the sample is reflective of the population distribution, then repeated sub-sampling of 

the sample will result in an unbiased and reliable estimate of the variance. OLMS will use the 

Rao and Wu (1988) method for bootstrap estimation of a variance. This method is summarized in 

Lohr (1999, p. 307).8

Degree of Accuracy

See above.

Unusual Problems

None.

Use of Periodic Rate Less Than Annually

Data collected under these surveys are one-time and are thus less frequent than annual.

B.3. Describe methods to maximize response rates and to deal with issues of

non-response. 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.

 

7 Additionally, because equation (8) defines weights for each respondent, the class-level indexing in equation (8) can 

be replaced by respondent-level indexing. That is, equation (8) defines a value for each respondent ( ~whj ).

8 The method of Rao and Wu (1988) has been coded into available software packages.
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EPA will employ a number of procedures to maximize response rates and to mitigate issues 

associated with non-response. A number of nonresponse issues may arise during the data collection 

process. Table B-4 summarizes issues related to nonresponse and the approach to handling those 

issues. EPA will analyze the known data on non-respondents (e.g., region, size, etc.) for patterns. 

This analysis will indicate whether the data collected through the survey will have any potential 

biases. 

Table B-4. Non-response Issues and Techniques Used to Minimize the Impact of Those 

Issues

Non-response Issue Techniques to Be Used to Minimize Impact of Nonresponse

Refusals—Observational unit 

refuses to take survey

 EPA will be using a professional survey firm that is 

skilled in converting refusals.

 EPA will replace refusals with similar households (e.g., 

within the same geographic region).

 EPA will develop a questionnaire that limits the burden 

imposed on observational units.

Not available—Observational 

unit not available at the time the 

phone survey firm calls

 The survey firm will call the household back up to three 

times before considering them non-respondents and 

excluding them from the sample.

 EPA will replace refusals with similar households (e.g., 

within the same geographic region).

Refusal to answer specific 

questions—Observational unit 

refuses to answer specific 

questions

 EPA will be using a professional survey firm that is 

skilled in converting refusals.

 EPA will develop a questionnaire that limits the burden 

imposed on observational units.

B.4. Describe any tests of procedures or methods to be undertaken. 

EPA will pre-test the survey instruments using a small set of households. The purpose of 

the pre-tests will be to assess the questionnaire validity in collecting the necessary data.

No other tests of procedures or methods will be used for these surveys. EPA expects that 

the sampling scheme and the implementation process are relatively straightforward and should 

be accomplished without need for testing the methods.

B5. 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 collect and/or analyze the information for the agency.

Dr. Lou Nadeau, ERG, (781) 674-7316.
06/22/13 Page 12

SECTION III: CONSUMER SURVEY (INTERNET-BASED)

B1. Describe, including a numerical estimate, the potential respondent universe and any 

sampling or other respondent selection method to be used. Data on the number of 

entities (e.g., establishments, state and local government units, households, 

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 rate for the collection as 

a whole. If the collection has been conducted previously, include the actual response 

rate achieved during the last collection.

The purpose of this survey is to increase EPA’s understanding of market barriers that 

exist with water-efficient products and services, develop messages that will address these 

barriers, and test the results of the findings in key markets. EPA will invite participants to 

provide feedback on promotions and messaging. EPA will use the data gathered to develop 

messaging for public service announcements. 

Approximately four hundred US adults will be invited to participate in the research effort. 

Only homeowners will be sampled, since renters are unlikely to be responsible for purchasing 

low-flow plumbing equipment. Data will be stratified by whether the individuals live in water 

rich or water poor areas of the nation. 

The goal of this research is to determine which methods of communicating water 

efficient-products are most effective (i.e., translate into the most positive attitudes toward and 

intentions to buy) to U.S. consumers. We are not trying to estimate a population parameter (e.g., 

such as general awareness of the WaterSense logo), rather we are comparing efficacy of 

communication techniques. Rule of thumb in this case is that we will need to use 20-30 

respondents in each communication condition. 

We will be drawing our sample using an electronic panel of homeowners and will not be 

using a random sample; thus, will not have information regarding nonresponse. Nonresponse 

bias is of concern when attempting to generalize from the sample estimate to a population 

parameter, but becomes somewhat unimportant when the goal is to determine differences 

between treatment groups. 

B2. Describe the procedures for the collection of information including: (a) statistical 

methodology for stratification and sample selection; (b) estimation procedures; (c) 

degree of accuracy needed for the purpose described in the justification; (d) unusual 

problems requiring specialized sampling procedures; and (e) any use of periodic 

(e.g., less frequent than annual) data collection cycles to reduce burden.

a) We will not be using a statistical methodology for stratification and sample selection since 

the goal of the research is to determine differences between groups.

b) We will use Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of

Covariance (MANCOVA) to test for differences between groups and to control for 

covariates.

c) A “by-invitation-only” only panel recruitment method is used by the on-line panel provider 

that will be collecting the data for this study. This means that only pre-validated individuals 

participate. Thus, a cross-section of “real” consumers, as opposed to regular survey takers, 
06/22/13 Page 13

are included in the sample. The panel to be used does not employ an “open” online panel 

recruitment method which simply allows individuals to self-select into the study. 

d) There are no unusual problems that will require a specialized sample procedures.

e) Data will not be collected periodically. This is a one-time study.

B3. Describe methods to maximize response rates and to deal with issues of nonresponse. The accuracy and reliability of information must be shown to be adequate 

for intended use. 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.

Since our purpose is to test for differences between groups, generalizability to the 

population at large (i.e., external validity) is less important than assurance that the experimental 

condition created the effect (i.e., internal validity). In such situations as ours, nonresponse bias is 

not a major concern in the study design.

B4. 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 tests may 

be submitted for approval separately or in combination with the main collection of 

data.

Pretesting of the questionnaire design and procedures will be conducted in two different 

ways. First, using the methods described in Dillman (2000), we will use a verbal protocol with 

less than ten home owners to gain a better understanding of how the target population is 

interpreting our questions and whether we have included the appropriate response categories.

Second, we will pretest the on-line survey to insure that it is working properly, is user-friendly

and that the data can be downloaded adequately. 

*Don A. Dillman (2000) Mail and Internet Surveys: The Tailored Design Method. John Wiley & Sons, Inc., NY, 

NY. 

B5. 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 collect and/or analyze the information for the agency

Dr. Lou Nadeau, ERG, (781) 674-7316.

REFERENCES

Cohen, Jacob, 1988. Statistical Power Analysis for the Behavioral Sciences, 2nd Edition, 

Lawrence Earlbaum Associates Publishers, Hillsdale, N.J.

Lohr, Sharon, 1999. Sampling: Design and Analysis, Duxbury Press, Pacific Grove, CA.
06/22/13 Page 14

Rao, J.N.K., and C.F.J. Wu, 1988. “Resampling Inference with Complex Survey Data,” Journal 

of the American Statistical Association, 83: 231-241.