EXCEED THE SPACE PROVIDED. This research investigates the relationship of age to measurement errors in survey-administered self-report questionnaires. The focus of the research is on the survey interview as a method of gathering social data, and the extent to which measurement errors assessed in such interviews vary as a function of the respondent's age. The overall aims of this project are to better understand the nature of survey measurement errors and the processes by which they are generated, and to make practical recommendations about the characteristics of survey questions that will improve the quality of data in surveys of the aging population. To accomplish these goals the research conducts a systematic analysis of the reliability of responses to survey questions using several nationally- representative panel data sets. First, we build upon our prior NSF-supported research using three surveys from the National Election Study (NES) series -- the 1956-58-60, 1972-74-76, and 1992-94-96 panel studies of the American electorate, and a fourth panel survey, the 1986-89-94 Americans' Changing Lives (ACL) study of health and well-being, to examine reliability by age, controlling for education. Second, we investigate these issues using two innovative panel surveys of middle-aged and older adults: the original Health & Retirement Study (HRS) panel study of preretirement men and women aged 51-61 assessed in 1992 (n=9,824), and reinterviewed in 1994, 1996, 1998 and 2000, and the parallel study of Asset and Health Dynamics (AHEAD) which interviewed adults aged 70 and above in 1993, and reinterviewed them in 1995, 1998 and 2000 (n= 7,447). The younger HRS (birth cohorts of 1931-41) and older AHEAD (birth cohorts of 1923 and before) respondents were asked many of the same questions, permitting the comparison of measurement errors across groups. Age-specific levels of reliability will be estimated for approximately 1,000 survey questions using a variety of state-of-the-art estimation strategies. Two basic approaches will be employed in the estimation of reliability- first the SEM-based maximum-likelihood approach for situations where it makes sense to assume continuous unobserved latent variables, and second the 'latent transition' models that are appropriate where the unobserved latent variables are latent classes. Within the SEM approach the research will empoy several different estimation strategies depending on the scale assumptions appropriate to the observed data, including standard Pearson-based covariance approaches for continuous variables, tetrachoric correlations for dichotomous variables and polychoric-based asymptotic covariance approach with weighted least squares estimation for ordinal variables. A major focus of the analysis is on age-related differences in the impact of the formal properties of survey questions (e.g., question content, length of question text, number and complexity of response options, and the provision of explicit 'Don't Know' response options) on reliability. Assembling information on reliability from these data sources can help improve knowledge about the strengths and weaknesses of survey data. It is expected that the results of this research will be relevant to the general task of uncovering the sources of age-related measurement errors in surveys and the improvement of methods of survey data collection across the life span through the application of this knowledge. PERFORMANCE SITE ========================================Section End===========================================

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG020673-03
Application #
6831190
Study Section
Special Emphasis Panel (ZRG1-RPHB-3 (04))
Program Officer
Patmios, Georgeanne E
Project Start
2003-02-15
Project End
2007-01-31
Budget Start
2005-03-01
Budget End
2007-01-31
Support Year
3
Fiscal Year
2005
Total Cost
$448,548
Indirect Cost
Name
Pennsylvania State University
Department
Type
Organized Research Units
DUNS #
003403953
City
University Park
State
PA
Country
United States
Zip Code
16802