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Analysis of matched cohort data

Author

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  • Peter Cummings

    (School of Public Health and Community Medicine, University of Washington, Seattle, WA)

  • Barbara McKnight

    (School of Public Health and Community Medicine, University of Washington, Seattle, WA)

Abstract

Matching is occasionally used in cohort studies; examples include studies of twins and some studies of traffic crashes. Analysis of matched cohort data is not discussed in many textbooks or articles and is not mentioned in the Stata manuals. Risk ratios can be estimated using matched-pair cohort data with Stata's mcc command. We describe a new command, csmatch, which can produce these risk ratios and is often more convenient. We briefly review flexible regression methods that can estimate risk ratios in matched cohort data: conditional Poisson regression and some versions of Cox regression. Copyright 2004 by StataCorp LP.

Suggested Citation

  • Peter Cummings & Barbara McKnight, 2004. "Analysis of matched cohort data," Stata Journal, StataCorp LP, vol. 4(3), pages 274-281, September.
    • Handle: RePEc:tsj:stataj:v:4:y:2004:i:3:p:274-281
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    References listed on IDEAS

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    1. Quinn McNemar, 1947. "Note on the sampling error of the difference between correlated proportions or percentages," Psychometrika, Springer;The Psychometric Society, vol. 12(2), pages 153-157, June.
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    Cited by:

    1. Kathryn C. Conlon & Kristina W. Kintziger & Meredith Jagger & Lydia Stefanova & Christopher K. Uejio & Charles Konrad, 2016. "Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health," IJERPH, MDPI, vol. 13(8), pages 1-23, August.
    2. Peter Cummings, 2009. "Methods for estimating adjusted risk ratios," Stata Journal, StataCorp LP, vol. 9(2), pages 175-196, June.
    3. Peter Cummings, 2011. "Estimating adjusted risk ratios for matched and unmatched data: An update," Stata Journal, StataCorp LP, vol. 11(2), pages 290-298, June.

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