Literature DB >> 22065944

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

Maria Paola Caria1, Rino Bellocco, Maria Rosaria Galanti, Nicholas J Horton.   

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.

Entities:  

Year:  2011        PMID: 22065944      PMCID: PMC3208350     

Source DB:  PubMed          Journal:  Stata J        ISSN: 1536-867X            Impact factor:   2.637


  4 in total

1.  Estimating and comparing univariate associations with application to the prediction of adult obesity.

Authors:  M S Pepe; R C Whitaker; K Seidel
Journal:  Stat Med       Date:  1999-01-30       Impact factor: 2.373

Review 2.  Regression analysis of multiple source and multiple informant data from complex survey samples.

Authors:  Nicholas J Horton; Garrett M Fitzmaurice
Journal:  Stat Med       Date:  2004-09-30       Impact factor: 2.373

3.  Early gender differences in adolescent tobacco use--the experience of a Swedish cohort.

Authors:  M R Galanti; I Rosendahl; A Post; H Gilljam
Journal:  Scand J Public Health       Date:  2001-12       Impact factor: 3.021

4.  Multiple informants: mortality associated with psychiatric disorders in the Stirling County Study.

Authors:  N J Horton; N M Laird; J M Murphy; R R Monson; A M Sobol; A H Leighton
Journal:  Am J Epidemiol       Date:  2001-10-01       Impact factor: 4.897

  4 in total
  1 in total

1.  Analysis of partially observed clustered data using generalized estimating equations and multiple imputation.

Authors:  Kathryn M Aloisio; Sonja A Swanson; Nadia Micali; Alison Field; Nicholas J Horton
Journal:  Stata J       Date:  2014-10-01       Impact factor: 2.637

  1 in total

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