I am using the RMS package in R to conduct a logistic regression that contains a three-way interaction. As part of my modelling approach, I have conducted chunk tests of the interaction (using Wald chi-square) followed by odds ratios for significant interactions. I have been asked by a reviewer to provide betas and standard errors for all factors in the model. I know how to obtain beta estimates for different levels of an interaction, but I can't find a way to obtain a single beta to represent the entire three-way interaction term. Is there any way of doing this with an
Model is predicting police outcome (court/no court) Independent variables are ethnicity (binary), age (continuous), sex (binary), previous violent charge (3 categories) and number of charges (3 categories).
Outcome~ rcs(Age,5) +
Violence + Sex +
N_Charges + rcs(Age,5)*
Ethnicity + rcs(Age,5)Sex +
Violence + rcs(Age,5)
*Ethnicity*Sex, x=TRUE, y=TRUE, fitter = lrm, xtrans = imp)
I am interested in obtaining the beta for the bolded interaction term.