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

Author

Listed:
  • Maria Paola Caria

    (Karolinska Institutet, Sweden)

  • Rino Bellocco

    (Karolinska Institutet, Sweden)

  • Maria Rosaria Galanti

    (Karolinska Institutet, Sweden)

  • Nicholas J. Horton

    (Smith College, Northampton, MA)

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.

Suggested Citation

  • Maria Paola Caria & Rino Bellocco & Maria Rosaria Galanti & Nicholas J. Horton, 2011. "The impact of different sources of body mass index assessment on smoking onset: An application of multiple-source information models," Stata Journal, StataCorp LLC, vol. 11(3), pages 386-402, September.
    • Handle: RePEc:tsj:stataj:v:11:y:2011:i:3:p:386-402
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    References listed on IDEAS

    as
    1. Nicholas Horton & Garrett Fitzmaurice, 2005. "Analysis of multiple source/multiple informant data in Stata," North American Stata Users' Group Meetings 2005 1, Stata Users Group.
    2. Ben Jann, 2005. "Making regression tables from stored estimates," Stata Journal, StataCorp LLC, vol. 5(3), pages 288-308, September.
    3. Zhiqiang Wang, 2007. "Two postestimation commands for assessing confounding effects in epidemiological studies," Stata Journal, StataCorp LLC, vol. 7(2), pages 183-196, June.
    4. Peter Cummings, 2009. "Methods for estimating adjusted risk ratios," Stata Journal, StataCorp LLC, vol. 9(2), pages 175-196, June.
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