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 de scribes the required elements for the annual reporting process, Sectio n 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 meth od 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 ex pected response rate for the collection as a
whole. If the collection has been conducted previously, include th e 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

2009 52 percent Promotional Partners

2008 30 percent
Manufacturers 2009 65 percent

10/30/09 Page 1Partner Type Reporting Year Response Rate

2008 41 percent
2009 30 percent Retailers/Distributors

2008 20 percent Irrigation Partners 2008-2009 N/A – reporting not required

2009 51 percent Total

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 pr ocedures, 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 resp onsibility to log the data. WaterSense contractor will receive shipment and sales data from manufact urer 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, part ners 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 sale s data, the WaterSense data manager provides a listing of reporting partners to the helpline staff. Helpline staff verify eligibility of the partner to re port by checking the listing of part ners in the manufacturer or retailer/distributor categor y. If the partner is not eligible to report, helpline staff contact the partner to discuss their partnershi p 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 not e the decision on the part ner’s reporting form. For manufacturers, the data manager will conduct on e additional step: the data manager, or her designee, will contact the license d 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 rese ll the products. After conf irming eligibility to submit data (i.e., data are from a bona fide pa rtner, 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 sh ipments (sales) excessive for what might be expected for a company of size reporting)?

• Is there evidence that the partner has provi ded estimated data rather than actual?

• Is there evidence that the partner has in cluded international shipments or sales?

10/30/09 Page 2If the answer to any of the above questions is ye s, ERG will contact the pa rtner to clarify. If the partner cannot sufficiently explain the data, th ey will not be included in subsequent data analyses.

B3. Describe methods to maximize response ra tes and to deal with issues of nonresponse. The accuracy and reliability of in formation 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 report ing process is stressed to part ners 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 answ er partner questions about the form

• Send emails and a postcard to remind partners of upcoming due dates

• Remind partners about reporti ng in quarterly newsletter

• Follow-up phone calls to non-reporting partners

• Coordination with a plumbing trade associ ation whose members ar e also WaterSense partners to encourage submi ssion of annual reporting forms

• Require that an annual reporting form is co mpleted 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 refinin g 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 th e main collection of

data.

EPA provided draft versions of the annual reporting form to se veral partners (fewer than 10) for comment and revised the form accordingl y. Upon the completion of each data collection cycle, EPA examines the responses, form, and pro cedures and identifies pot ential changes for the following year based on common ques tions or issues that arise.

B5. Provide the name and telephone number of individuals consul ted 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 (E RG) 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.

10/30/09 Page 3SECTION II: CONSUMER AW ARENESS PHONE SURVEY

B.1. Describe (including a numerical estimate ) the potential respondent universe and any sampling or other respondent selection meth ods 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 th e universe as a whole and for each of the strata in the proposed sample. Indicate ex pected response rates for the collection as
a whole. If the collection had been conducte d previously, include the actual response rate achieved during the last collection.

The target population for these two surveys wi ll be households in the United States. This corresponds to the target population of the Wa terSense program. The sampling population will be adults living in households that are surv eyed. There are 116.8 million households in the United States according to the most recen tly available Census Bureau numbers. 1 From this, EPA will select a sample of 400 re spondents for each survey. The jus tification 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. house holds are readily available for this type of

survey.

EPA has not previously conducted these surv eys, thus it cannot estimate the expected response based on past experience. Evaluation practitioners have documented that survey response rates have been declin ing worldwide in recent years. 2 In a recent study 3 of response rates for 205 telephone surveys c onducted in the same survey la b over a three-year period, study authors found that response rate s varied from fewer than 10 per cent to greater than 90 percent response, with the largest number of surveys fa lling in the 25 – 45 percent range. Further, the study authors found that response rates are aff ected by contextual va riables 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 le ngth results in a 7 pe rcent 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; Sing er, 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.

10/30/09 Page 4B.2. Describe the procedures for the collection of information including:

• Statistical methodolog y for stratification and sample selection, • Estimation procedure, • Degree of accuracy needed for the purpose described in the justification, • Unusual problems requiring spec ialized sampling procedures, and • Any use of periodic (less frequently th an annual) data collection cycles to

reduce burden.

Statistical Method for Stratifi cation and Sample Selection

This section discusses the st atistical methods for stratifica tion 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 ne eded to meet a set of specific statistical criteria for the survey data. Choosing a sample si ze is a three-step proce ss. First, statistical criteria are set; second, an init ial sample size is chosen base d 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 th e large universe size. Th e 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 para meter 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 corr ectly 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 pow er and confidence and, therefore, most of the emphasis is in choosing a reasonable precision. To se lect sample size using these criteria, EPA has used statistical power an alysis 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 di fference (in units of the key question) that one is willing be away from the population parame ter of interest. The para meter of interest for

10/30/09 Page 5this 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 (perce ntage of households aware of the program) and the second reflects a change in a proportion over time. Thus, precisi on will need to be in terms of percentage points. EPA has determined that th e 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 de termined that the sample should be able to detect three to five point ch ange in awareness over time. 4 For example, if aw areness is found to be 5 percent in this survey and a subsequent surv ey finds awareness to be 10 percent, the sample sizes for each survey should be large enough to fi nd that change to be st atistically significant.

Power

The power of a statistical test is one minus th e probability of a Type II error (not rejecting a false hypothesis), or the probabili ty of correctly reje cting a false hypothesis. In this sense, power corresponds to finding the specified effect si ze (i.e., precision) when that effect in fact exists. Traditional hypothesis tests set, by defau lt, power to 50 percent. Following Cohen’s (1988) suggestion, EPA will use 80 percent power. T hus, 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 hypothesi s. For purposes of sampling, confidence defines the likelihood that the populati on mean will be contained in the interval around the sample mean defined by the precisi on 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 base d on the methods of Cohen (1988), Chapter 6, which provides power analytic methods for dete cting 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 awaren ess in the universe. Setting a sample size for proportions requires either havi ng some knowledge of proporti on for the population beforehand, or making an assumption on the proportion for the population. EPA expect s that awareness of

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.

10/30/09 Page 6WaterSense 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 fro m all baseline levels, detection of a four point increase in awareness for baseline awaren ess in the two to five percent range of baseline awareness, and detection of a three point incr ease 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

Precision: Increase in Awareness to be

Detected Assumed
Baseline
Level of
Awareness in
the Universe 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

pr p =

+ − 0 1

2 100 2 2 . arcsin arcsin

where n 0.1 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.

10/30/09 Page 7Estimation Procedure

Estimation of population parameters (means, totals, and variances) will be done by appropriately weighting the sample values. Th e 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 es timated as the reciprocal of the selection probabilities. These can be estimated as:

w N

n w hj h

h h = = (6)

where N h is the population for stratum h and n h 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 proba bility (above) and a response pr obability. To estimate response probabilities, EPA will divide th e respondents in each survey into a small number of classes (strata). The exact classes for each survey will de pend on the nature of the data available for each group. The response probabilities are then:

θ

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

θ (8)

The weighted total for any question in these survey s can be found using the following
formula: 6

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.

10/30/09 Page 8$

~ Y w hj hj j J

h H h

=

== 

## ∑∑

11 y (9)

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

H

is the total number of st rata used in the survey, j indexes sample respondents within each

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

, ~ w hj is the nonresponse-adjusted
sampling weight for the j th unit in stratum h

, 7 and y hj is the value for th e variable/question y for
the j th unit in stratum h . Estimates of the population means can then be found as:

$ $

~ Y Y

w hj j J

h H h =

== 

## ∑∑

11 (10)

Estimation of the variance for the expressions in equations (9) and ( 10) will require more complex methods. The variance of both expressions w ill 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 ar e not fixed). To calculate these variances, EPA will use a bootstrap method. Bootstrap met hods involve repeated sub-sampling (with replacement) of the selected sample and calcula ting the variance from the repeated samples. In theory, if the sample is reflective of the populat ion distribution, then re peated sub-sampling of the sample will result in an unbiased and reliab le 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-tim e and are thus less frequent than annual.

B.3. Describe methods to maximize respons e 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 ba sed on sampling, a special justification must

7 Additionally, because equation (8) defi nes weights for each respondent, the clas s-level indexing in equation (8) can be replaced by respondent-level indexing. That is, equation (8) defines a value for each respondent ( ~ w hj ).

8 The method of Rao and Wu (1988) has been coded into available software packages.

10/30/09 Page 9be provided for any collection that will not yield “reliable” data that can be generalized to
the universe studied. EPA will employ a number of proc edures 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 issu es related to nonresponse and the approach to handling those issues. EPA will analyze the know n data on non-respondents (e.g., re gion, 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 w ith 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 w ith 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 procedu res or methods to be undertaken.

EPA will pre-test the survey instruments us ing a small set of households. The purpose of the pre-tests will be to asse ss 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 pro cess are relatively straightforward and should be accomplished without need for testing the methods.

B5. Provide the name and telephone number of individuals consul ted on statistical aspects of the design and the name of th e 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

10/30/09 Page 10SECTION III: CONSUMER SU RVEY (INTERNET-BASED)

B1. Describe (including a numerical estimate ) the potential respondent universe and any sampling or other respondent selection meth od to be used. Data on the number of entities (e.g., establishments, state a nd 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 conducte d previously, include the actual response rate achieved during the last collection.

The purpose of this survey is to increase unde rstanding of market barr iers that exist with water-efficient products and services, develop messa ges that will address th ese barriers, and test the results of the findings in key markets. Partic ipants 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 stra tified 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., tran slate 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 util ize 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 nonr esponse 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 differ ences 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 st ratification and sample selection since the goal of the research is to dete rmine differences between groups. b) Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of Covariance (MANCOVA) will be used to test for differe nces between groups and to control for
covariates.

10/30/09 Page 11c) A “by-invitation-only” only pa nel recruitment method is used by the on-line panel provider that will be collecting the data for this study. This means that only pre-vali dated individuals participate. Thus, a cross-secti on of “real” consumers, as oppos ed 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 indi viduals to self-selec t into the study. d) There are no unusual problems that will require specialized sample procedures. e) Data will not be collected period ically. This is a one-time study.

B3. Describe methods to maximize respons e rates and to deal with issues of non- response. The accuracy and reliability of in formation 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 yiel d “reliable” data that can be generalized
to the universe studied.

Since the purpose is to test for differe nces between groups, ge neralizability to the population at large (i.e., external validity) is less important than assurance that the experimental condition created the effect (inter nal 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 tim e, panel members earn online currency which they can redeem for their choi ce of a variety of rewards.

B4. Describe any tests of procedures or methods to be undertaken. Testing is encouraged as an effective means of refinin g 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 th e main collection of

data.

Pretesting of the questionnaire design and pr ocedures will be conduc ted 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 bette r understanding of how th e target population is interpreting questions and whet her the appropriate response categories are included. Second, the on-line survey will be pretested with a group of st udents studying social marketing to insure that it is working properly, is user-f riendly and that the data ca n 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 consul ted on statistical aspects of the design and the name of th e 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

10/30/09 Page 12Qualtrics 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 , 2 nd 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.

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