Abstract

R. M. Baron and D. A. Kenny (1986; see record 1987-13085-001) provided clarion conceptual and methodological guidelines for testing mediational models with cross-sectional data. Graduating from cross-sectional to longitudinal designs enables researchers to make more rigorous inferences about the causal relations implied by such models. In this transition, misconceptions and erroneous assumptions are the norm. First, we describe some of the questions that arise (and misconceptions that sometimes emerge) in longitudinal tests of mediational models. We also provide a collection of tips for structural equation modeling (SEM) of mediational processes. Finally, we suggest a series of 5 steps when using SEM to test mediational processes in longitudinal designs: testing the measurement model, testing for added components, testing for omitted paths, testing the stationarity assumption, and estimating the mediational effects.

Keywords

Structural equation modelingPsychologyCLARIONLongitudinal dataCausal modelLongitudinal studyEconometricsStatistical hypothesis testingCognitive psychologyComputer scienceStatisticsMathematicsData mining

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Publication Info

Year
2003
Type
article
Volume
112
Issue
4
Pages
558-577
Citations
3240
Access
Closed

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David A. Cole, Scott E. Maxwell (2003). Testing Mediational Models With Longitudinal Data: Questions and Tips in the Use of Structural Equation Modeling.. Journal of Abnormal Psychology , 112 (4) , 558-577. https://doi.org/10.1037/0021-843x.112.4.558

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DOI
10.1037/0021-843x.112.4.558