Dear all I am struggling with how to deal with missing values using geeglm. I know that geeglm only works with complete datasets, but I cannot seem to get the na.omit function to work. For example
assuming DataMiss contains 3 columns, each of which has missing observations, and an id column with no missing info then identifies the clusters. Outcome: 2 level integer Predictor: numeric variable Confounder: 3 level integer If I "manually" remove the missing values then run the model, there is no problem. #remove missing values data<-subset(DataMiss, !is.na(outcome) & !is.na(predictor) & !is.na(confounder)) #run the model model<-geeglm(outcome~predictor+confounder, family=binomial(link = "logit"), data=data, corstr='ar1', id=id, std.err="san.se") However, I don't always want to have to run this extra step. The R instructions seem to indicate that na.omit should work, as shown below model<-geeglm(outcome~predictor+confounder, family=binomial(link = "logit"), data=na.omit(DataMiss), corstr='ar1', id=id, std.err="san.se") But I keep getting this error. Any help would be greatly appreciated! Error in family$linkfun(mustart) : Argument mu must be a nonempty numeric vector -- View this message in context: http://r.789695.n4.nabble.com/Missing-values-and-geeglm-tp3675622p3675622.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
