The impact of different sources of body mass index assessment on smoking onset: An application of multiple-source information models

Maria Paola Caria (), Rino Bellocco (), Maria Rosaria Galanti () and Nicholas Horton
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Maria Paola Caria: Karolinska Institutet, Sweden
Rino Bellocco: Karolinska Institutet, Sweden
Maria Rosaria Galanti: Karolinska Institutet, Sweden

Stata Journal, 2011, vol. 11, issue 3, 386-402

Abstract: Multiple-source data are often collected to provide better information of some underlying construct that is difficult to measure or likely to be missing. In this article, we describe regression-based methods for analyzing multiple-source data in Stata. We use data from the BROMS Cohort Study, a cohort of Swedish adolescents who collected data on body mass index that was self-reported and that was measured by nurses. We draw together into a single frame of reference both source reports and relate these to smoking onset. This unified method has two advantages over traditional approaches: 1) the relative predictiveness of each source can be assessed and 2) all subjects contribute to the analysis. The methods are applicable to other areas of epidemiology where multiple-source reports are used. Copyright 2011 by StataCorp LP.

Keywords: multiple informants; multiple-source predictors; regression analysis; generalized estimating equations; missing data (search for similar items in EconPapers)
Date: 2011
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