Literature DB >> 22399826

The Use of Propensity Scores in Mediation Analysis.

Booil Jo1, Elizabeth A Stuart, David P Mackinnon, Amiram D Vinokur.   

Abstract

Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid conclusions, especially regarding the relation between the mediator and outcome variables. Propensity score methods offer an alternative whereby the propensity score is used to compare individuals in the treatment and control groups who would have had the same value of the mediator had they been assigned to the same treatment condition. This article describes the use of propensity score weighting for mediation with a focus on explicating the underlying assumptions. Propensity scores have the potential to offer an alternative estimation procedure for mediation analysis with alternative assumptions from those of standard mediation analysis. The methods are illustrated investigating the mediational effects of an intervention to improve sense of mastery to reduce depression using data from the Job Search Intervention Study (JOBS II). We find significant treatment effects for those individuals who would have improved sense of mastery when in the treatment condition but no effects for those who would not have improved sense of mastery under treatment.

Entities:  

Year:  2011        PMID: 22399826      PMCID: PMC3293166          DOI: 10.1080/00273171.2011.576624

Source DB:  PubMed          Journal:  Multivariate Behav Res        ISSN: 0027-3171            Impact factor:   5.923


  23 in total

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Authors:  Constantine E Frangakis; Donald B Rubin
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2.  A general approach to causal mediation analysis.

Authors:  Kosuke Imai; Luke Keele; Dustin Tingley
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3.  Propensity score estimation with boosted regression for evaluating causal effects in observational studies.

Authors:  Daniel F McCaffrey; Greg Ridgeway; Andrew R Morral
Journal:  Psychol Methods       Date:  2004-12

4.  Using latent outcome trajectory classes in causal inference.

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5.  Impact of conceptions of ability on self-regulatory mechanisms and complex decision making.

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6.  Sensitivity Analysis and Bounding of Causal Effects With Alternative Identifying Assumptions.

Authors:  Booil Jo; Amiram D Vinokur
Journal:  J Educ Behav Stat       Date:  2011-08

7.  Impact of a preventive job search intervention on the likelihood of depression among the unemployed.

Authors:  R H Price; M Van Ryn; A D Vinokur
Journal:  J Health Soc Behav       Date:  1992-06

8.  Average causal effects from nonrandomized studies: a practical guide and simulated example.

Authors:  Joseph L Schafer; Joseph Kang
Journal:  Psychol Methods       Date:  2008-12

9.  Causal inference in randomized experiments with mediational processes.

Authors:  Booil Jo
Journal:  Psychol Methods       Date:  2008-12

10.  On the use of propensity scores in principal causal effect estimation.

Authors:  Booil Jo; Elizabeth A Stuart
Journal:  Stat Med       Date:  2009-10-15       Impact factor: 2.373

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  20 in total

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Authors:  Wenjing Zheng; Mark J van der Laan
Journal:  Int J Biostat       Date:  2012-01-06       Impact factor: 0.968

2.  Sensitivity plots for confounder bias in the single mediator model.

Authors:  Matthew G Cox; Yasemin Kisbu-Sakarya; Milica Miočević; David P MacKinnon
Journal:  Eval Rev       Date:  2014-03-28

3.  Prevention of problem behavior through annual family check-ups in early childhood: intervention effects from home to early elementary school.

Authors:  Thomas J Dishion; Lauretta M Brennan; Daniel S Shaw; Amber D McEachern; Melvin N Wilson; Booil Jo
Journal:  J Abnorm Child Psychol       Date:  2014

4.  A Viable Alternative When Propensity Scores Fail: Evaluation of Inverse Propensity Weighting and Sequential G-Estimation in a Two-Wave Mediation Model.

Authors:  Matthew J Valente; David P MacKinnon; Gina L Mazza
Journal:  Multivariate Behav Res       Date:  2019-06-20       Impact factor: 5.923

5.  Statistical approaches for enhancing causal interpretation of the M to Y relation in mediation analysis.

Authors:  David P MacKinnon; Angela G Pirlott
Journal:  Pers Soc Psychol Rev       Date:  2014-07-25

6.  Mediation analysis for count and zero-inflated count data.

Authors:  Jing Cheng; Nancy F Cheng; Zijian Guo; Steven Gregorich; Amid I Ismail; Stuart A Gansky
Journal:  Stat Methods Med Res       Date:  2017-01-08       Impact factor: 3.021

7.  Intravenous Acetaminophen Reduces Length of Stay Via Mediation of Postoperative Opioid Consumption After Posterior Spinal Fusion in a Pediatric Cohort.

Authors:  Vanessa A Olbrecht; Lili Ding; Kristie Spruance; Monir Hossain; Senthilkumar Sadhasivam; Vidya Chidambaran
Journal:  Clin J Pain       Date:  2018-07       Impact factor: 3.442

8.  Comparing models of change to estimate the mediated effect in the pretest-posttest control group design.

Authors:  Matthew J Valente; David P MacKinnon
Journal:  Struct Equ Modeling       Date:  2017-02-08       Impact factor: 6.125

9.  Improving Our Ability to Evaluate Underlying Mechanisms of Behavioral Onset and Other Event Occurrence Outcomes: A Discrete-Time Survival Mediation Model.

Authors:  Amanda J Fairchild; Winston E Abara; Amanda C Gottschall; Jenn-Yun Tein; Ronald J Prinz
Journal:  Eval Health Prof       Date:  2013-12-02       Impact factor: 2.651

10.  Identification and efficient estimation of the natural direct effect among the untreated.

Authors:  Samuel D Lendle; Meenakshi S Subbaraman; Mark J van der Laan
Journal:  Biometrics       Date:  2013-04-23       Impact factor: 2.571

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