Dear UseRs,
I built varying coefficient models (in mgcv) for two groups separately, with one explanatory and one moderator variable (see the example below). # ------- # Example: # ------ # generate moderator variable (can the same for both groups) modvar <- c(1:1000) # generate group1 values x1 <- rnorm(1000) y1 <- scale(cbind(1,poly(modvar,2))%*%c(1,2,1)*x1 + rnorm(1000,0,0.3)) # generate group2 values x2 <- rnorm(1000) y2 <- scale(cbind(1,poly(modvar,2))%*%c(-1,0.5,-1)*x2 + rnorm(1000,0,0.3)) # separate models for each group mg1 <- gam(y1~s(modvar,by=x1)) mg2 <- gam(y2~s(modvar,by=x2)) Having done this, the next step would be to test if there is a significant difference between the modvar-dependency of the coefficient of the X values (i.e. to check if the coefficients vary in a different manner in the two groups): # unified model Y <- c(y1,y2) X <- c(x1,x2) M <- c(modvar,modvar) Group <- rep(c(0,1),each=1000) ??? And at this point I do not know how to proceed. Maybe a permutation approach would be helpful, but I would be more comfortable with a built-in solution. I tried to find similar threads but had no success. Any help is highly appreciated. Regards, Denes [[alternative HTML version deleted]]
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