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 /TARGET_OPTIONS REFERENCE=0 DISTRIBUTION=BINOMIAL LINK=LOGIT /FIXED EFFECTS=questionnairescore Treatment Facetype questionnairescore*Treatment questionnairescore*Facetype Treatment*Facetype **questionnairescore*Treatment*Face**type USE_INTERCEPT=TRUE /RANDOM USE_INTERCEPT=TRUE SUBJECTS=id COVARIANCE_TYPE=VARIANCE_COMPONENTS /RANDOM EFFECTS=trial USE_INTERCEPT=FALSE COVARIANCE_TYPE=VARIANCE_COMPONENTS /BUILD_OPTIONS TARGET_CATEGORY_ORDER=ASCENDING INPUTS_CATEGORY_ORDER=ASCENDING MAX_ITERATIONS=100 CONFIDENCE_LEVEL=95 DF_METHOD=RESIDUAL COVB=MODEL.