EONS Annual Survey Justification Part B

EONS Annual Survey Justification Part B.docx

Employers of National Service annual Survey

OMB: 3045-0178

Document [docx]
Download: docx | pdf

Employer of National Service Annual Survey

Shape1

SUPPORTING STATEMENT FOR PAPERWORK REDUCTION ACT SUBMISSIONS

B. COLLECTIONS OF INFORMATION EMPLOYING STATISTICAL METHODS


B1. Describe (including 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 potential respondent universe for the Employers of National Service Survey consists of all organizations enrolled in the initiative. The current number of organizations enrolled in Employers of National Service is 372 establishments. There will be no other sampling used. We hope to have 75% of all currently enrolled employers respond to the survey. This data has not been previously collected.

Exhibit 1. Strata for Employers of National Service Survey.

Type

# of Employers in network

Federal Government

18

Institution of Higher Education

14

Nonprofit Organization

239

Other

6

Private Sector

53

School District

12

State or Local Government

30

Grand Total

372


B2. 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 frequent than annual) data collection cycles to reduce burden.

This survey will be administered on a webform located on nationalserivce.gov. Reasonable accommodations will be made for any employers that request the survey in a format other than the webform. This survey will be made available to all currently enrolled establishments in the Employers of National Service network; there is no sample selection. Information provided will be at the discretion of the employers. This information is only collected to enroll new employers and on an annual basis thereafter.


B3. 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.

The Employers of National Service survey will employ a number of strategies to maximize response rates. Messages will be sent through a quarterly newsletter, emails, and social media. A second wave of messages will be targeted at non-responders. Targeted phone calls will be the last method employed, if necessary. The information will be accurate and reliable regardless of response rate. This collection is not based on sampling.


B4. Describe any tests of procedures or methods to be undertaken.

Testing is not required for this survey.


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

CNCS will analyze the information itself. The individuals at CNCS assigned to this project include:

  • Cali Cornacchia, Eli Segal Fellow, 202-606-6821

  • Erin Dahlin, Deputy Chief of Programs, 202-606-6931

  • Diana Epstein, Ph.D., Senior Research Analyst, Research and Evaluation, 202-606-7564



File Typeapplication/vnd.openxmlformats-officedocument.wordprocessingml.document
AuthorCornacchia, Cali
File Modified0000-00-00
File Created2021-01-24

© 2024 OMB.report | Privacy Policy