Dear Stata users,
I have a dataset that looks something like this - each person has
observations on 2 hips and 2 knees and I wish to calcuate the odds ratio
of hips to knees, taking account of the clustering within person using
robust standard errors.
id hip knee row
1 1 0 1
1 1 0 2 (1=replaced, 2=not replaced)
2 . 1 3
2 0 1 4
3 1 0 5
3 0 . 6
4 1 0 7
4 . . 8
I have tried all of the following commands
logistic hip knee, cluster(id)
xtlogit hip knee, i(id) or
svymean hip, by(knee)
but all of them drop any record (line) with a missing value (.), so in
the above dataset, rows 3, 6 and 8 would be dropped, despite there being
a non-missing observation in the other group that should be included in
the analysis. This gives incorrect estimates for the odds ratio when you
calculate them by hand from the equivalent 2x2 table. e.g from the
above example, if I was calculating the OR by hand I would get
yes (1) no (0)
hips 4 2
knees 2 4
OR = (4X4)/(2X2) = 4
However if all the rows with the missing values are dropped, you get
yes (1) no (0)
hips 4 1
knees 1 4
OR = (4X4)/(1X1) = 16
Any ideas or suggestions on how to calculate the correct odds ratio and
robust s.e. would be much appreciated.
Louise
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