# How do you assess a three-way interaction in a generalized multi-level model?

I am unsure which statistical tests I should use in order to follow-up my three-way interaction. I used to split my file and run the analysis twice per group, but as I read in the paper by Hayes & Matthes, 2009, Behavior Research Methods, this is not a good approach.

I have a centered continuous variable (questionnaire score), one dichotomous variable and one variable called facetype with three categories. I have 6 trials per facetype condition per participant, so each participant has multiple lines in my SPSS file. My dependent variable is binary.

I use the generalized linear model to analyze this data. The fixed effects show a significant three-way interaction, and I would like to interpret the interaction by for example testing the significance of one slope. I have no idea how to do this with multilevel data.

GENLINMIXED
/DATA_STRUCTURE SUBJECTS=id*trial
/FIELDS TARGET=in_team_yes_no TRIALS=NONE OFFSET=NONE