Supporting_Statement_Part_B_2021QSAR (002)

Supporting Statement Outline – Sample

NOTE: Complete Part B for Survey ICR Requests

SUPPORTING STATEMENT – PART B

B.  COLLECTIONS OF INFORMATION EMPLOYING STATISTICAL METHODS

If the collection of information employs statistical methods, it should be indicated in Item 17 of OMB Form 83-I, and the following information should be provided in this Supporting Statement:

1.  Description of the Activity

Describe the potential respondent universe and any sampling or other method used to select respondents.  Data on the number of entities covered in the collection should be provided in tabular form for the universe as a whole and for each of the strata in the proposed sample.  Indicate the expected response rates for the collection as a whole, as well as the actual response rates achieved during the last collection, if previously conducted.

The survey targets sexual assault prevention and response responders. Working with SAPRO, we estimate the approximate numbers of members in the frame to be certified SARCs (n=~500), VAs (n=~28,500), and SVCs/VLCs/SVPs (n=~1,000). The survey will be sent to all responders (i.e., a census). Based on the 2018 QSAR survey that had a 23% response rate, we estimate a 25% response rate. To achieve sufficient statistical analytical power, we will include a census of the population of interest in the study to achieve sufficient coverage. During the fielding period, questionnaires will be distributed to all responders who meet the above criteria and estimate the number to be approximately 30,000 individuals in total.

2.  Procedures for the Collection of Information

Describe any of the following if they are used in the collection of information:

1. Statistical methodologies for stratification and sample selection;

Stratification for sample selection does not apply for a census study.

2. Estimation procedures;

OPA weights the eligible respondents in order to make inferences about the entire population of interest. The weighting methodology utilizes standard weighting processes. First, we assign a base weight to the sampled member based on the reciprocal of the selection probability. Second, OPA adjusts for known eligibility status for members in the population who did not reply to the survey or did not provide enough information in their response to determine whether they were eligible population members in terms of the survey scope. This adjustment is the reciprocal of the probability that a sample member responds with enough information to determine eligibility status. Third, OPA adjusts for survey completion. This third adjustment accounts for members in the sample who replied with enough information to determine that they were eligible for the survey, but who did not complete a sufficient quantity of the survey questionnaire to be considered a “usable” record/response. This adjustment is the reciprocal of the conditional probability of completing the survey according to a defined threshold, given that the respondent is eligible. Lastly, OPA applies an adjustment to attempt to mitigate potential nonresponse bias that may be present under the assumption that survey responses may be Missing at Random (MAR).

3. Degree of accuracy needed for the Purpose discussed in the justification;

OPA creates variance strata so precision measures can be associated with each estimate. We produce precision measures for reporting categories using 95% confidence intervals with the goal of achieving a precision of 5% or less (e.g, 80% (+/- 5%) of SARCs are satisfied with their job).

4. Unusual problems requiring specialized sampling procedures; and

None.

5. Use of periodic or cyclical data collections to reduce respondent burden.

To reduce burden on this population, OPA conducts the QSAR every three years.

3.  Maximization of Response Rates, Non-response, and Reliability

Discuss methods used to maximize response rates and to deal with instances of non-response.  Describe any techniques used to ensure the accuracy and reliability of responses is adequate for intended purposes.  Additionally, if the collection is based on sampling, ensure that the data can be generalized to the universe under study.  If not, provide special justification.

OPA offers the survey via the Web and uses reminder emails to maximize response rates. To reduce respondent burden, web-based surveys use “smart skip” technology to ensure respondents only answer questions that are applicable to them. To deal with instances of nonresponse, OPA adjusts for nonresponse in the weighting methodology. To ensure the accuracy and reliability of responses, OPA conducts a nonresponse bias (NRB) analysis on some surveys. Historically OPA has found little evidence of significant NRB during these studies; however, OPA statisticians consider the risk of NRB high and consider it likely the largest source of error in OPA surveys. OPA uses appropriate weighting to ensure the survey data can be generalized to the universe under study.

4.  Tests of Procedures

Describe any tests of procedures or methods to be undertaken.  Testing of potential respondents (9 or fewer) is encouraged as a means of refining proposed collections to reduce respondent burden, as well as to improve the collection instrument utility.  These tests check for internal consistency and the effectiveness of previous similar collection activities.

Not applicable.

5.  Statistical Consultation and Information Analysis

a. Provide names and telephone number of individual(s) consulted on statistical aspects of the design.

Mr. David McGrath, Branch Chief; Statistical Methods Team, Methods, Analysis, and Systems Support, Office of People Analytics (OPA); (571) 372- 0983.

Ms. Wendy Barboza, Team Lead; Statistical Methods Team, Methods, Analysis, and Systems Support, Office of People Analytics (OPA); (571) 372-1099.

b. Provide name and organization of person(s) who will actually collect and analyze the collected information.

The data will be collected by Fors Marsh Group (FMG), which is OPA’s analysis contractor. Ms. Amanda Barry is Director of Military Workplace Climate Research at FMG and Mr. Rich Maitland is a FMG survey programmer.

The data will be analyzed by OPA analysts. Ms. Lisa Davis and Dr. Rachel Breslin oversee this effort.

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