

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
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