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?? [[alternative HTML version deleted]]