SME_wave3_SUPPORTING STATEMENT PART B

SME_wave3_SUPPORTING STATEMENT PART B.docx

Small and Medium-Sized Business Complex Event COVID-19 Survey (Wave 3)

OMB: 0693-0088

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SUPPORTING STATEMENT PART B - (Questions and guidance for Responses)


Agencies are instructed to complete Supporting Statement Part B if they are using statistical methods, such as sampling, imputation, or other statistical estimation techniques; most research collections or program evaluations should also complete Part B. If an agency is planning to conduct a sample survey as part of its information collection, Part B of the ICR supporting statement must be completed, and an agency should also complete relevant portions of Part B when conducting a census survey (collections that are sent to the entire universe or population under study). For example, an agency doing a census of a small, well- defined population may not need to describe sampling procedures requested in Part B, but it should address what pretesting has taken place, what its data collection procedures are, how it will maximize response rates, and how it will deal with missing unit and item data.

Agencies conducting qualitative research studies or program evaluations, including case studies or focus groups, should also complete the relevant sections of Part B to provide a more complete description of the use of the information and the methods for collecting the information.

B. Collections of Information Employing Statistical Methods

  1. 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 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 sample will be drawn from respondents to Waves 1 and 2 of data collection on this topic.  These individuals are all self-identified small business operators. There are 3000 respondents (complete data collected in previous surveys) from which respondents to the current proposed Wave 3 may be drawn. In cases where respondents to Wave 1 and Wave 2 indicated that they would like to be contacted for additional data collection, they are eligible for recontact. We have the capacity to contact 2200 respondents across these earlier waves for potential participation in the current data collection. 

Going from Wave 1 to Wave 2 for repeat respondents we had a 25 % response rate. We also had a refreshment sample of new respondents in Wave 2, which accounts for the additional respondents from which we can draw the current sample for this data collection. We offered no remuneration in those data collections. It is expected and supported in the literature that offering reasonable remuneration for time spent on the online data collection proposed here will increase response rates significantly. Those eligible for outreach indicated in the Wave 2 data collection that they want to be contacted and are thus already willing to engage. The use of remuneration has a high likelihood of moving the response rate to 60-80 % of those whom will be contacted. 

  1. Describe the procedures for the collection of information including:

Given the importance of considering small business operators who have experienced natural hazards during the COVID-19 transmission period, there will be a stratified sampling approach employed. The strata will be: (1) businesses reporting natural hazard impact and (2) operators not reporting natural hazard impacts. These will be drawn from our existing sample. Within each strata, random sampling will occur based on the percent of total sample each strata represents. Emails will be sent out that offer respondents the opportunity to answer either the long or short DCI version. When the desired 300 respondents to the long DCI is obtained that option will be muted and the remaining respondents contacted will only have the option to complete the short DCI. 


  1. 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.

One reminder email will be sent to respondents who do not engage with the DCI. This reminder will be sent two weeks after initial contact. The universe of longitudinal respondents obtained in previous data collections (Wave 1 and Wave 2) show representativeness for the main area of inquiry.

The response rate will be maximized through the use of remuneration offered to operators for time spent completing the data collection. 


  1. 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 information.


No testing was conducted for this information collection.

  1. Provide the name and telephone number of individuals consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.

Jennifer Helgeson, [email protected] Applied Economics Office, Engineering Lab, NIST

Juan Fung, [email protected] Applied Economics Office, Engineering Laboratory, NIST

Payam Aminpour, [email protected], Applied Economics Office, Engineering Laboratory, NIST

File Typeapplication/vnd.openxmlformats-officedocument.wordprocessingml.document
AuthorHelgeson, Jennifer F. (Fed)
File Modified0000-00-00
File Created2021-06-09

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