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Hello, I'm not a Stata user so I'm trying to reproduce Stata results that are given to me in R. I would like to use a GLM with a complementary log-log function. The stata code I have is: glm c IndA fia, family(binomial s) link(cloglog) offset(offset) The R code is: glmt <- glm(data=dataset, c ~ IndA + fia, offset = offset, family = binomial(link = cloglog)) Which yields different results from the Stata output. I think the difference is in the variable s that is included in the binomi...

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...t;-[c(indx,indy),] std<-sd(S[,"f"]) t<-round(max(q[,"a"]),0) u<-round(min(q[,"a"]),0) colnames(v)<-c("a") D<-q[,"a"] d<-density(D) pdf('L') for (h in length(s[["a"]])) { for (i in length(S[["a"]])) { inda<-which(q[h,"a"]==q[h,"d"]) indb<-which(q[i,"a"]==q[i,"e"]) R<-(s[c(inda),"f"]+s[c(indb),"f"])/2 indh<-which(abs(q[,"b"]-R)<=(2*std)) indi<-which(abs(q[,"c"]-R)<=(2*std)) A<-q[indh,c("a&qu...

...e = 'a') > B <- data.frame(Tid = Tid[2:4], dfName = 'b') > C <- data.frame(Tid = Tid[1:3], dfName = 'c') # then use the sqldf library > library(sqldf) > sqldf() # to create indices on the Tid variable shared across data.frames > sqldf('create index indA on A(Tid)') > sqldf('create index indB on B(Tid)') > sqldf('create index indC on C(Tid)') # check to make sure everything is there > sqldf('select * from sqlite_master') # doing a natural join (implicitly on Tid) # does not give the expected joins > sqldf(&...