New Recommendations for Testing Indirect Effects in Mediational Models: The Need to Report and Test Component Paths - Université Grenoble Alpes Accéder directement au contenu
Article Dans Une Revue Journal of Personality and Social Psychology Année : 2018

New Recommendations for Testing Indirect Effects in Mediational Models: The Need to Report and Test Component Paths

Résumé

In light of current concerns with replicability and reporting false-positive effects in psychology, we examine Type I errors and power associated with 2 distinct approaches for the assessment of mediation, namely the component approach (testing individual parameter estimates in the model) and the index approach (testing a single mediational index). We conduct simulations that examine both approaches and show that the most commonly used tests under the index approach risk inflated Type I errors compared with the joint-significance test inspired by the component approach. We argue that the tendency to report only a single mediational index is worrisome for this reason and also because it is often accompanied by a failure to critically examine the individual causal paths underlying the mediational model. We recommend testing individual components of the indirect effect to argue for the presence of an indirect effect and then using other recommended procedures to calculate the size of that effect. Beyond simple mediation, we show that our conclusions also apply in cases of within-participant mediation and moderated mediation. We also provide a new R-package that allows for an easy implementation of our recommendations.
Fichier non déposé

Dates et versions

hal-01989994 , version 1 (04-02-2019)

Identifiants

Citer

Vincent Yzerbyt, Dominique Muller, Cédric Batailler, Charles M Judd. New Recommendations for Testing Indirect Effects in Mediational Models: The Need to Report and Test Component Paths. Journal of Personality and Social Psychology, 2018, 115 (6), pp.929-943. ⟨10.1037/pspa0000132⟩. ⟨hal-01989994⟩
118 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More