Literature DB >> 23788819

Using Potential Outcomes to Understand Causal Mediation Analysis: Comment on.

Kosuke Imai1, Booil Jo, Elizabeth A Stuart.   

Abstract

In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by Maxwell, Cole, and Mitchell (2011).

Entities:  

Year:  2011        PMID： 23788819      PMCID： PMC3685497          DOI： 10.1080/00273171.2011.606743

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


  18 in total

1.  Principal stratification in causal inference.

Authors:  Constantine E Frangakis; Donald B Rubin
Journal:  Biometrics       Date:  2002-03       Impact factor: 2.571

2.  Mediation in experimental and nonexperimental studies: new procedures and recommendations.

Authors:  Patrick E Shrout; Niall Bolger
Journal:  Psychol Methods       Date:  2002-12

3.  A general approach to causal mediation analysis.

Authors:  Kosuke Imai; Luke Keele; Dustin Tingley
Journal:  Psychol Methods       Date:  2010-12

4.  Identifiability and exchangeability for direct and indirect effects.

Authors:  J M Robins; S Greenland
Journal:  Epidemiology       Date:  1992-03       Impact factor: 4.822

5.  Establishing a causal chain: why experiments are often more effective than mediational analyses in examining psychological processes.

Authors:  Steven J Spencer; Mark P Zanna; Geoffrey T Fong
Journal:  J Pers Soc Psychol       Date:  2005-12

6.  Matching methods for selection of subjects for follow-up.

Authors:  Elizabeth A Stuart; Nicholas S Ialongo
Journal:  Multivariate Behav Res       Date:  2010-07-01       Impact factor: 5.923

7.  Using latent outcome trajectory classes in causal inference.

Authors:  Booil Jo; Chen-Pin Wang; Nicholas S Ialongo
Journal:  Stat Interface       Date:  2009-01-01       Impact factor: 0.582

8.  Causal inference in randomized experiments with mediational processes.

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

9.  Causal inference in longitudinal comparative effectiveness studies with repeated measures of a continuous intermediate variable.

Authors:  Chen-Pin Wang; Booil Jo; C Hendricks Brown
Journal:  Stat Med       Date:  2014-02-27       Impact factor: 2.373

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
View more
  9 in total

1.  Editorial: Introduction to the Special Section on Causal Inference in Cross Sectional and Longitudinal Mediational Models.

Authors:  Stephen G West
Journal:  Multivariate Behav Res       Date:  2011-09-30       Impact factor: 5.923

2.  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

3.  Estimating and testing pleiotropy of single genetic variant for two quantitative traits.

Authors:  Qunyuan Zhang; Mary Feitosa; Ingrid B Borecki
Journal:  Genet Epidemiol       Date:  2014-07-12       Impact factor: 2.135

4.  Identifying Mechanisms of Behavior Change in Psychosocial Alcohol Treatment Trials: Improving the Quality of Evidence from Mediational Analyses.

Authors:  John W Finney
Journal:  J Stud Alcohol Drugs       Date:  2018-03       Impact factor: 2.582

5.  Checking Behavior, Fear of Recurrence, and Daily Triggers in Breast Cancer Survivors.

Authors:  Emily C Soriano; Rosmeiry Valera; Elizabeth C Pasipanodya; Amy K Otto; Scott D Siegel; Jean-Philippe Laurenceau
Journal:  Ann Behav Med       Date:  2019-03-01

6.  Clarifying causal mediation analysis for the applied researcher: Defining effects based on what we want to learn.

Authors:  Trang Quynh Nguyen; Ian Schmid; Elizabeth A Stuart
Journal:  Psychol Methods       Date:  2020-07-16

7.  Applying causal mediation methods to clinical trial data: What can we learn about why our interventions (don't) work?

Authors:  R Whittle; G Mansell; P Jellema; D van der Windt
Journal:  Eur J Pain       Date:  2016-10-14       Impact factor: 3.931

Review 8.  Are Manipulation Checks Necessary?

Authors:  David J Hauser; Phoebe C Ellsworth; Richard Gonzalez
Journal:  Front Psychol       Date:  2018-06-21

9.  The Indirect Effect of Age Group on Switch Costs via Gray Matter Volume and Task-Related Brain Activity.

Authors:  Jason Steffener; Yunglin Gazes; Christian Habeck; Yaakov Stern
Journal:  Front Aging Neurosci       Date:  2016-07-13       Impact factor: 5.750
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.