title: Testing mediational models with longitudinal data: questions and tips in the use of structural equation modeling.
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.
authors.affiliation: Psychology and Human Development, Vanderbilt University, Nashville, TN 37203, USA. david.cole@vanderbilt.edu
authors.forename: David A
authors.initials: DA
authors.lastname: Cole
authors.forename: Scott E
authors.initials: SE
authors.lastname: Maxwell
mesh_terms: D003430:Cross-Sectional Studies; D003625:Data Collection / Q000706:statistics & numerical data; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D011594:Psychometrics / Q000706:statistics & numerical data*; D011599:Psychopathology / Q000706:statistics & numerical data*; D015203:Reproducibility of Results