Hello,
I want to test a regression model with neuroticism as focal predictor,
agreeableness as moderator and RT variability as dependent measure (covariates:
attentional control and mean RT). Previously, I have used the modprobe macro in
SPSS by Andrew Hayes for this (for full reference see end of message). I am in
the process of transitioning to R, however, and would like to learn how to run
a similar routine there. I have set up my regression model as follows:
m3<-lm(data=stp2_sub2,
all_SD~Neuroticism*Agreeableness+Attentional.Control+all_RT, na.action=na.omit)
# full interaction model
m33<-lm(data=stp2_sub2,
all_SD~Neuroticism+Agreeableness+Attentional.Control+all_RT, na.action=na.omit)
# reduced model
I know that I can obtain F-change and p-change, using:
anova(m3, m33) # provides F-change and p-change
What I still don’t know yet is how to obtain the R squared change value, which
gives me the effect size of the interaction effect. Any advice on this would be
much appreciated.
Best,
Marcel
Reference:
Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing
interactions in OLS and logistic regression: SPSS and SAS implementations.
Behavior Research Methods, 41(3), 924–36. doi:10.3758/BRM.41.3.924
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