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Dear R community, I have data on beta&standard error (for the main effect of variable x), stratified by sex for my dataset. I wish to calculate the sex-interaction effect (as beta&se) from these two stratified datasets. Is there a package to do this? If not, any advice how to do it manually? Thank you very much and best regards, Georg. ************************ Georg Ehret, JHU,

...on: X <- kronecker(diag(1,3),x) Y <- c(y) # stack the y in a vector # residual covariance matrix for each observation covar <- kronecker(sigma,diag(1,N)) # GLS betas covariance matrix inv.sigma <- solve(covar) betav <- solve(t(X)%*%inv.sigma%*%X) # GLS mean parameter estimates betam <- betav%*%t(X)%*%inv.sigma%*%Y ----- end of code ----

...,mub) ? ? ? ? ? ? ? ? ?^ Reference to unimplemented intrinsic `MATMUL' at (^) (assumed EXTERNAL) LDDPdensity.f:430: ? ? ? ? ? ? xty2=matmul(xtx2,mub) ? ? ? ? ? ? ? ? ?^ Invalid declaration of or reference to symbol `matmul' at (^) [initially seen at (^)] LDDPdensity.f:458: ? ? ? ? ? ? ? ?betam=matmul(xtx,xty) ? ? ? ? ? ? ? ?^ Expression at (^) has incorrect data type or rank for its context LDDPdensity.f:515: ? ? ? ? ? ? xty=matmul(sbeta0i,m0) ? ? ? ? ? ? ^ Expression at (^) has incorrect data type or rank for its context LDDPdensity.f:535: ? ? ? ? ? ? ? ?xty=xty+matmul(xtx2,betawork)...