Literature DB >> 26736048

Commentary: Are Three Waves of Data Sufficient for Assessing Mediation?

Charles S Reichardt1.   

Abstract

Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even with longitudinal data, simple autoregressive structural equation models can imply the existence of indirect effects when only direct effects exist and the existence of direct effects when only indirect effects exist.

Year:  2011        PMID: 26736048     DOI: 10.1080/00273171.2011.606740

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


  7 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.  Predicting the Intention to Use Condoms and Actual Condom Use Behaviour: A Three-Wave Longitudinal Study in Ghana.

Authors:  Enoch Teye-Kwadjo; Ashraf Kagee; Hermann Swart
Journal:  Appl Psychol Health Well Being       Date:  2016-12-07

4.  Investigating the impact of the time interval selection on autoregressive mediation modeling: Result interpretations, effect reporting, and temporal designs.

Authors:  Lijuan Wang; Qian Zhang
Journal:  Psychol Methods       Date:  2019-09-23

5.  SAS® Macros for Computing Causal Mediated Effects in Two- and Three-Wave Longitudinal Models.

Authors:  Matthew J Valente; David P MacKinnon
Journal:  SAS Glob Forum       Date:  2018

6.  On the Use of Mixed Markov Models for Intensive Longitudinal Data.

Authors:  S de Haan-Rietdijk; P Kuppens; C S Bergeman; L B Sheeber; N B Allen; E L Hamaker
Journal:  Multivariate Behav Res       Date:  2017-09-28       Impact factor: 5.923

7.  Time to Intervene: A Continuous-Time Approach to Network Analysis and Centrality.

Authors:  Oisín Ryan; Ellen L Hamaker
Journal:  Psychometrika       Date:  2021-06-24       Impact factor: 2.290

  7 in total

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