American Journal of Epidemiology Vol. 150, No. 11: 1165-1178
Copyright © 1999 by The Johns Hopkins University School of Hygiene and Public Health
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Determination of Risk Factor Associations with Questionnaire Outcomes: A Methods Case Study
1Department of Biostatistics, School of Hygiene and Public Health, The Johns Hopkins University Baltimore, MD
2Dana Center for Preventive Ophthalmology, Wilmer Eye Institute, Johns Hopkins Medical Institutions Baltimore, MD
3Lions Low Vision, Center, Johns Hopkins Medical Institutions Baltimore, MD
Reprint requests to Dr. Karen Bandeen-Roche, Department of Biostatistics, School of Hygiene and Public Health, The Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205.
Increasingly in biomedical studies, health status is inferred through a series of questionnaire item responses. Challenges for analyzing associations between such responses and risk factors include multiplicity many indicators must be combined to derive summary statements about health status, and measurement error persons' self report fluctuates due to causes other than substantive health changes. In order to deal with these challenges, the authors propose a strategy which comprises three methods: 1) score the item responses, then regress the score on predictors; 2) regress each item response on predictors, accounting for within person associations; and 3) summarize and analyze the item responses jointly, using a latent variable model. The authors develop modeling and diagnostic procedures for method 3. They then show how the three method analytic strategy can be used to solve the problem of determining which aspects of vision are associated with self reported functioning in activities that require seeing at a distance. They demonstrate that methods 2 and 3 illuminate basic findings from method 1 by adding specificity, describing patterns as well as severities of health impairments, and identifying isolated items that relate to risk factors differentially than others. They conclude that the three method strategy specifies how risk factors determine questionnaire based health outcomes substantially better than any of the methods in isolation. Am J Epidemiol 1999; 150:1165–78
aging; discrete data; goodness-of-fit; latent class; latent variable; multivariate regression; vision
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