model<-geeglm(outcome~predictor+confounder, family=binomial(link = "logit"),
data=na.omit(DataMiss), corstr='ar1', id=id, std.err="san.se")
There could be other variables in DataMiss that have many missing values, so
when you apply na.omit() on DataMiss, you may be ending up with an empty
data.f
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
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