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st: RE: Re: Analysis of binary cluster data with missing values


From   "Nick Cox" <n.j.cox@durham.ac.uk>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: RE: Re: Analysis of binary cluster data with missing values
Date   Thu, 13 Nov 2003 11:39:07 -0000

I assume "row" means "leg" or "limb".

I don't think this is a Stata issue,
as Stata's behaviour appears correct
given the data and what you ask of it.

Please explain why you think your
by-hand analysis is correct. I
don't think you can collapse the
table in this way. A test of
that is that if you reverse the
table you cannot recover even a subset
of the data correctly, as you do not have
complete data on 6 limbs. Rather, you have
complete data on 5 limbs only,
as Stata is telling you.

Nick
n.j.cox@durham.ac.uk

Louise Linsell

> 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.

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