Literature DB >> 33536726

Causal Mediation Programs in R, Mplus, SAS, SPSS, and Stata.

Matthew J Valente1, Judith J M Rijnhart2, Heather L Smyth3, Felix B Muniz3, David P MacKinnon3.   

Abstract

Mediation analysis is a methodology used to understand how and why an independent variable (X) transmits its effect to an outcome (Y) through a mediator (M). New causal mediation methods based on the potential outcomes framework and counterfactual framework are a seminal advancement for mediation analysis, because they focus on the causal basis of mediation analysis. There are several programs available to estimate causal mediation effects, but these programs differ substantially in data set up, estimation, output, and software platform. To compare these programs, an empirical example is presented, and a single mediator model with XM interaction was estimated with a continuous mediator and a continuous outcome in each program. Even though the software packages employ different estimation methods, they do provide similar causal effect estimates for mediation models with a continuous mediator and outcome. A detailed explanation of program similarities, unique features, and recommendations are discussed.

Entities:  

Keywords:  causal effects; counterfactual; estimation; mediation; software

Year:  2020        PMID: 33536726      PMCID: PMC7853644          DOI: 10.1080/10705511.2020.1777133

Source DB:  PubMed          Journal:  Struct Equ Modeling        ISSN: 1070-5511            Impact factor:   6.125


  12 in total

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Journal:  Mol Psychiatry       Date:  2022-08-10       Impact factor: 13.437

2.  Impact of financial support on the prognosis of HER2-positive breast cancer from 2002 to 2020: a prospective cohort from western China.

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3.  Child maltreatment, anxiety and depression, and asthma among British adults in the UK Biobank.

Authors:  Yueh-Ying Han; Qi Yan; Wei Chen; Juan C Celedón
Journal:  Eur Respir J       Date:  2022-03-17       Impact factor: 33.795

4.  Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis.

Authors:  Judith J M Rijnhart; Matthew J Valente; Heather L Smyth; David P MacKinnon
Journal:  Prev Sci       Date:  2021-11-16

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Authors:  Zengliang Jiang; Lai-Bao Zhuo; Yan He; Yuanqing Fu; Luqi Shen; Fengzhe Xu; Wanglong Gou; Zelei Miao; Menglei Shuai; Yuhui Liang; Congmei Xiao; Xinxiu Liang; Yunyi Tian; Jiali Wang; Jun Tang; Kui Deng; Hongwei Zhou; Yu-Ming Chen; Ju-Sheng Zheng
Journal:  Nat Commun       Date:  2022-05-30       Impact factor: 17.694

6.  Assessing Potential Outcomes Mediation in HIV Interventions.

Authors:  Heather L Smyth; Eileen V Pitpitan; David P MacKinnon; Robert E Booth
Journal:  AIDS Behav       Date:  2021-03-19

Review 7.  Assessing the Robustness of Mediation Analysis Results Using Multiverse Analysis.

Authors:  Judith J M Rijnhart; Jos W R Twisk; Dorly J H Deeg; Martijn W Heymans
Journal:  Prev Sci       Date:  2021-07-16

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Journal:  Transl Psychiatry       Date:  2022-04-11       Impact factor: 7.989

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Journal:  Int J Environ Res Public Health       Date:  2021-04-03       Impact factor: 3.390

Review 10.  Mediation analysis methods used in observational research: a scoping review and recommendations.

Authors:  Judith J M Rijnhart; Sophia J Lamp; Matthew J Valente; David P MacKinnon; Jos W R Twisk; Martijn W Heymans
Journal:  BMC Med Res Methodol       Date:  2021-10-25       Impact factor: 4.615

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