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Causal Mediation Analysis using Stata

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  • Joerg Luedicke

    (StataCorp)

Abstract

Causal inference is an essential goal in many research areas and aims at identifying and quantifying causal effects. By decomposing causal effects into direct and indirect effects, causal mediation provides further insight into underlying mechanisms through which causal effects operate. This talk presents the basic theoretical framework for causal mediation analysis and discusses a variety of examples using Stata's -mediate- command. Examples will include linear and generalized linear models using a variety of outcome and mediator variables as well as different types of treatments.

Suggested Citation

  • Joerg Luedicke, 2023. "Causal Mediation Analysis using Stata," German Stata Conference 2023 08, Stata Users Group.
    • Handle: RePEc:boc:dsug23:08
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    File URL: http://repec.org/dsug2023/Luedicke_DEStataConf2023.pdf
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