JSM 2004 - Toronto

Abstract #300631

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Activity Number: 295
Type: Topic Contributed
Date/Time: Wednesday, August 11, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Health Policy Statistics
Abstract - #300631
Title: Inclusion of Sampling Weights in Mixed-Effects Models: A Comparison of Two Methods
Author(s): Marianne Bertolet*+ and Joel Greenhouse and Howard Seltman and Kelly Kelleher
Companies: Carnegie Mellon University and Carnegie Mellon University and Carnegie Mellon University and Ohio State University
Address: Dept. of Statistics, Pittsburgh, PA, 15213,
Keywords: mixed-effects models ; sampling weights
Abstract:

Hierarchical models can provide valuable information when analyzing survey data. Because many health policy decisions are based on data collected by surveys, this type of research contributes to health policy research. As examples of health policy applications, Pfeffermann et al. (1998) analyzed a survey of psychiatric morbidity which looked at the relationship between demographic characteristics on the prevalence of psychiatric diseases. As another example, Korn and Graubard (2003) analyzed data from the Hispanic Health and Nutrition Examination Survey to analyze height-for-age percentiles in the Mexican-American community. For the survey analysis to provide meaningful results, the sampling weights must be properly incorporated. This research will help explain the differences between the methods, show with simulations the strengths and weaknesses of the methods, and provide software to make the methods more accessible to health policy researchers.

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