# SURVEY DESIGN ACKNOWLEDGING NONRESPONSE

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 1993 · $142,031

## Abstract

One of the most common methods of scientific inquiry in demographic
research in the sample survey, which permits inference to large diverse
natural populations. One theoretical foundation of that inference rests on
complete measurement of all sample units; that is, the absence of unit
nonresponse. When sample persons who fail to participate differ on key
health-related variables from those who do participate, nonresponse error
can threaten inference both for descriptive and structural model-based
estimates. The efficacy both of efforts to reduce nonresponse through data
collection strategies and of statistical postsurvey adjustment for
nonresponse rest on (at least implicit) theories of survey participation.
The proposed project builds on four years of prior investigation of
nonresponse features of several large U.S. national household surveys and
the theoretical principles inductively derived from qualitative
investigations of survey participation. Based on that work the
investigators have encouraged the enrichment of observational and other
measures of attributes of the interviewer, neighborhood, household, sample
person, and features of the interaction between interviewer and sample
person. The collection of these data is specified at the design stage of
a survey by a designer who anticipates the fact that nonresponse will
occur.  The data are used to guide nonresponse reduction activities,
decisions to terminate efforts to increase response rates, as well as
statistical models for postsurvey adjustment. The proposed project
evaluates the utility of some of these design features for the Health and
Retirement Survey (HRS) and the upcoming Asset and Health Dynamics of the
Oldest Old (AHEAD). The specific aims of the project are an examination of
the characteristics of HRS nonrespondents relative to those of respondents
and correlates of HRS nonresponse; construction of alternative postsurvey
nonresponse adjustment techniques, evaluated through sensitivity analysis
on important HRS analyses and variance properties of the resulting
estimators; construction of estimates of nonresponse error for key HRS
descriptive statistics; development of cost and error models for
nonresponse, evaluating the real tradeoff decisions investigators face
between continuing to expend data collection resources to increase
response rate and limiting or eliminating further expenditures; and a set
of proposed design features for the second wave interviewing of HRS and
the AHEAD project informative of nonresponse error features of the
studies.

## Key facts

- **NIH application ID:** 3123804
- **Project number:** 1R01AG012105-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **SAM.gov UEI:** GNJ7BBP73WE9
- **Principal Investigator:** ROBERT M GROVES
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 1993
- **Award amount:** $142,031
- **Award type:** 1
- **Project period:** 1993-09-30 → 1996-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/3123804

## Citation

> US National Institutes of Health, RePORTER application 3123804, SURVEY DESIGN ACKNOWLEDGING NONRESPONSE (1R01AG012105-01). Retrieved via MORVS 2026-10-25 from https://api.morvs.ai/grant/nih/3123804. Licensed CC0.

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