title: Statistical mediation analysis with a multicategorical independent variable.
abstract: Virtually all discussions and applications of statistical mediation analysis have been based on the condition that the independent variable is dichotomous or continuous, even though investigators frequently are interested in testing mediation hypotheses involving a multicategorical independent variable (such as two or more experimental conditions relative to a control group). We provide a tutorial illustrating an approach to estimation of and inference about direct, indirect, and total effects in statistical mediation analysis with a multicategorical independent variable. The approach is mathematically equivalent to analysis of (co)variance and reproduces the observed and adjusted group means while also generating effects having simple interpretations. Supplementary material available online includes extensions to this approach and Mplus, SPSS, and SAS code that implements it.
authors.affiliation: Department of Psychology, The Ohio State University, Columbus, Ohio, USA.
authors.forename: Andrew F
authors.initials: AF
authors.lastname: Hayes
authors.forename: Kristopher J
authors.initials: KJ
authors.lastname: Preacher
mesh_terms: D000704:Analysis of Variance; D015984:Causality; D015987:Effect Modifier, Epidemiologic; D006801:Humans; D016013:Likelihood Functions; D008432:Mathematical Computing; D015233:Models, Statistical; D011589:Psychology, Experimental / Q000706:statistics & numerical data*; D013223:Statistics as Topic