Merry Christmas everyone:
I have the following data(mydat) and would like to fit a conditional logistic
regression model considering "weights".
id case exposure weights
1 1 1 2
1 0 0 2
2 1 1 2
2 0 0 2
3 1 1 1
3 0 0 1
4 1 0 2
4 0 1 2 The R function"clogit" is for such purposes but
it ignores weights. I tried function"mclogit" instead which seems that it
considers the weights
option:##############################################################options(scipen=999)library(mclogit)#
create the above data frameid = c(1,1,2,2,3,3,4,4)case =
c(1,0,1,0,1,0,1,0)exposure = c(1,0,1,0,1,0,0,1)weights =
c(2,2,2,2,1,1,2,2)(mydata = data.frame(id,case,exposure,weights)) fit =
mclogit(cbind(case,id) ~ exposure,weights=weights,
data=mydata)summary(fit)######################################################################
The answer,however, doesn't seem to be correct. Could anyone pleaseprovides me
with some solution to this? Thanks in advance,Keramat Nourijelyani,PhD
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