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Two-stage individual participant data meta-analysis and generalized forest plots

Author

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  • David J. Fisher

    (MRC Clinical Trials Unit at University College London)

Abstract

In this article, I describe a command, ipdmetan, that facilitates twostage individual participant data meta-analysis of any measure of effect and its standard error by fitting a specified model to data from each study. The command can estimate random effects and heterogeneity statistics and include additional covariates and interactions. If individual participant data are available for certain studies and aggregate data for others, ipdmetan allows them to be combined in one analysis. This command can produce detailed and flexible forest plots, including ones outside the context of formal meta-analysis.

Suggested Citation

  • David J. Fisher, 2015. "Two-stage individual participant data meta-analysis and generalized forest plots," Stata Journal, StataCorp LP, vol. 15(2), pages 369-396, June.
    • Handle: RePEc:tsj:stataj:v:15:y:2015:i:2:p:369-396
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    Citations

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    Cited by:

    1. David Fisher, 2018. "admetan: A new, comprehensive meta-analysis command," London Stata Conference 2018 06, Stata Users Group.
    2. Asteria Brylka & Dieter Wolke & Sebastian Ludyga & Ayten Bilgin & Juliane Spiegler & Hayley Trower & Anna Gkiouleka & Markus Gerber & Serge Brand & Alexander Grob & Peter Weber & Kati Heinonen & Eero , 2021. "Physical Activity, Mental Health, and Well-Being in Very Pre-Term and Term Born Adolescents: An Individual Participant Data Meta-Analysis of Two Accelerometry Studies," IJERPH, MDPI, vol. 18(4), pages 1-14, February.
    3. David Bilén & Anna Dreber & Magnus Johannesson, 2021. "Are women more generous than men? A meta-analysis," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 7(1), pages 1-18, September.

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