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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