Three responses to your question
1. Missing values in R are denoted by "NA". When reading in your data you want to use
the "na.strings" option so that the internal form of the data has missing values properly
denoted.
2. If this is done, then coxme will notice the missings and remove them, you do not
need to do anything. Your second question of "how to use the missing data" is a much
deeper statistical one. Multiple imputation would be the obvious way to proceed, but it
is complex and I have no experience with respect to how it would work with a mixed effects
Cox model.
3. Your note implies that output was attached. Note that r-help strips away all
attachments, so none of us saw it.
Terry Therneau
On 12/19/2014 05:00 AM, r-help-requ...@r-project.org wrote:
Hi all,
I have a data set like this:
Test.cox file:
V1 V2 V3 Survival Event
ann 13 WTHomo 4 1
ben 20 * 5 1
tom 40 Variant 6 1
where "*" indicates that I don't know what the value is for V3 for Ben.
Remainder of message excluded
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