PART B: COLLECTION OF INFORMATION EMPLOYING STATISTICAL METHODS

Part B applies to three WaterSense data collection efforts: a census survey 

of all partners and two

consumer surveys, one of which uses sampling techniques. Section I describes 

the required

elements for the annual reporting process, 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

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, 

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 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 all organizational partners (promotional 

partners,

manufacturers, and retailers/distributors,) via annual reporting each year 

from 2010 - 2013.

Beginning in 2011, irrigation partners, will also be required to report. As 

of April 2009,

WaterSense has 1,286 partners. This is a census survey and no sampling 

methods will be used.

Table B-1 summarizes the number of partners by type

B-1: WaterSense Partners by Partner Type, April 2009

Partner Type

Number

Promotional Partners

419

Manufacturers

83

Retailers/Distributors

104

Irrigation Partners

680

Total

1,286
Table B-2 summarizes the actual response rate received during previous data 

collections.

B-2: WaterSense Partner Reporting in 2008 and 2009

Partner Type

Reporting Year

Response Rate

Promotional Partners

2009

52 percent

2008

30 percent

Manufacturers

2009

65 percent
2008

41 percent

Retailers/Distributors

2009

30 percent

2008

20 percent

Irrigation Partners

2008-2009

N/A – reporting not required

Total

2009

51 percent

2008

31 percent

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

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

The WaterSense Helpline will receive Promotional Partner Annual Reporting 

forms via

fax, e-mail or U.S. mail. It is the Helpline’s responsibility to log the 

data. WaterSense contractor

will receive shipment and sales data from manufacturer and 

retailer/distributor partners. The data

will be recorded on annual 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 or sales data, 

the WaterSense

data manager provides a listing of reporting partners to the helpline staff. 

Helpline staff verify

eligibility of the partner to report by checking the listing of partners in 

the manufacturer or

retailer/distributor 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. For

manufacturers, the data manager will conduct one additional step: the data 

manager, or her

designee, will contact the licensed certifying body that issued the 

WaterSense label to the

manufacturer, to ensure that the manufacturer is in fact the holder of 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. After confirming 

eligibility to

submit data (i.e., data are from a bona fide partner, shipment data are from 

a manufacturer

partner who holds the original certification file), the data manager will 

review each submission

to determine:

• Are there internal inconsistencies in the report (e.g., number of 

WaterSense products

shipped (sold) exceeds the total number of products shipped (sold))?

• Are the data unrealistic for the given partner (e.g., are the shipments 

(sales) 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.

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 partners to commit to submitting 

annual reports.

The importance of the annual reporting process 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 and a postcard to remind partners of upcoming due dates

• Remind partners about reporting in quarterly newsletter

• Follow-up phone calls to non-reporting partners

• Coordination with a plumbing trade association whose members are also 

WaterSense

partners to encourage submission of annual reporting forms

• Require that an annual reporting form is completed in order to receive an 

award or

recognition from EPA/WaterSense

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 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 (ERG) is the task manager for the 

census

survey 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.
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, 

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 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 116.8 million 

households in the

United States according to the most recently available Census Bureau 

numbers.1 From 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.2 In a recent 

study3 of 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 – 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 (listed versus random-digit dialing)

• Minutes per piece of sample (effort)

• Amount of time the survey was in the field.

A ten-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://www.census.gov/population/socdemo/hh-fam/cps2008/tabAVG1.xls.

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.
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, and

• Any use of periodic (less frequently 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
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.

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?), and

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

statistically

significant increase in awareness between surveys?)

The first reflects estimation of a proportion (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 (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.4 For 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 (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

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:

()nnprp=

+-

01210022.

arcsinarcsin

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.
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.

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:

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:

wNnwhjhhh== (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:

.ksumofweightsforrespondentsinksumofweightsforselectedsampleink=

()

()

(7)

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

respondent in class k

and stratum h becomes:

~wNnhkhhk=

1. (8)
The weighted total for any question in these surveys can be found using the 

following

formula:6
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.

$~YwhjhjjJhHh=

==

SS11

(9)

where $Yis 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

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:

$

$

~

YYwhjjJhHh=

==

SS11

(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.

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. Nonresponse Issues and Techniques Used to Minimize the Impact of 

Those

Issues

Nonresponse 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
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, 

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 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 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. Participants will be invited to 

provide feedback on

promotions and messaging.

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 a program or logo), rather we are comparing 

efficacy of

communication techniques. The survey will utilize 20-30 respondents in each 

communication

condition.

The sample will be drawn using an electronic panel of homeowners and will 

not be using

a random sample; thus, information regarding nonresponse is not available. 

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

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

a) A statistical methodology will not be used for stratification and sample 

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

b) Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of 

Covariance

(MANCOVA) will be used 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,

will be 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 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 the 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 (internal validity). In such situations, 

nonresponse bias is not a major

concern in the study design.

Incentives and reward programs are used to increase the response rate. 

Specifically,

Qualtics (the panel owner) compensates the panel members based on the amount 

of time they

spend answering questions. For each unit of time, panel members earn online 

currency which

they can redeem for their choice of a variety of rewards.

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), a verbal protocol 

will be used with

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

population is

interpreting questions and whether the appropriate response categories are 

included. Second, the

on-line survey will be pretested with a group of students studying social 

marketing 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

Laura Harwood, ERG, (703) 841-0589, Dr. Lou Nadeau, ERG, (781) 674-7316
Qualtrics Corporation will be collecting the data via an electronic consumer 

panel. The firm’s

phone number is 1-800-340-9194.

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.

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.