Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Neidert says decreasing relevance of marriage reflected in growing percent of one-person households

House says resolving socioeconomic inequalities, not spending more on health care, will improve health in America

Kusunoki, Hall, and Barber find obese teen girls less likely to use birth control


Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Elizabeth Bruch wins ASA award for paper in mathematical sociology

Next Brown Bag

PSC Brown Bags will be back fall 2015

Improving on analyses of self-reported data in a large-scale health survey by using information from an examination-based survey

Publication Abstract

Schenker, N., Trivellore Raghunathan, and I. Bondarenko. 2010. "Improving on analyses of self-reported data in a large-scale health survey by using information from an examination-based survey." Statistics in Medicine, 29(5): 533-545.

Common data sources for assessing the health of a population of interest include large-scale surveys based on interviews that often pose questions requiring a self-report, such as, 'Has a doctor or other health professional ever told you that you have < health condition of interest >?' or 'What is your (height/weight)?' Answers to such questions might not always reflect the true prevalences of health conditions (for example, if a respondent misreports height/weight or does not have access to a doctor or other health professional). Such 'measurement error' in health data could affect inferences about measures of health and health disparities. Drawing on two surveys conducted by the National Center for Health Statistics, this paper describes an imputation-based strategy for using clinical information from an examination-based health survey to improve on analyses of self-reported data in a larger interview-based health survey. Models predicting clinical values from self-reported values and covariates are fitted to data from the National Health and Nutrition Examination Survey (NHANES), which asks self-report questions during an interview component and also obtains clinical measurements during a physical examination component. The fitted models are used to multiply impute clinical values for the National Health Interview Survey (NHIS), a larger survey that obtains data solely via interviews. Illustrations involving hypertension, diabetes, and obesity suggest that estimates of health measures based on the multiply imputed clinical values are different from those based on the NHIS self-reported data alone and have smaller estimated standard errors than those based solely on the NHANES clinical data. The paper discusses the relationship of the methods used in the study to two-phase/two-stage/valiclation sampling and estimation, along with limitations, practical considerations, and areas for future research. Published in 2009 by John Wiley & Sons, Ltd.

DOI:10.1002/sim.3809 (Full Text)

Country of focus: United States of America.

Browse | Search : All Pubs | Next