Resampling under the null hypothesis instead of case resampling will preserve the correlations and distributional characteristics of the data and allow you to perform hypothesis testing. For more information, please refer to Westfall and Young (1993).
This brief post presents a function to implement the free step-down re-sampling p-value adjustment for multiple-testing for regression models. It is an adaptation of the R code presented in Foulkes (2009, pp. 114-119), but it implements the minP method in addition to the maxT method.
UPDATE: Please see the following post for an all-in-one solution: RePROCESS Model 1
This post was was inspired by Nicholas Michalak’s Novum R-ganum blog posts on reproducing Hayes’ PROCESS Model 1 in R. He has two posts where he presents the R code for examining a continuous × continuous moderation and a dichotomous × continuous moderation.
However, a quick Google search suggests a paucity of information for conducting moderation analyses using a multicategorical moderating variables.
Therefore, this post will outline how to run the PROCESS Model 1 with a multicategorical moderator (M) in R. We will examine how to code the M variable, simulate some data, run the PROCESS analyses in both SPSS and R, and compare the results from both software packages.