On 17 Samh 2005, at 05:24, Susan Donath wrote:
I have a small dataset (n=12 children) with time to event data for
each eye
(24 eyes). There are 2 subgroups (of the eyes), group 1 has less
severe
disease, group 2 has more severe disease. A child can have any
combination
of these (eg left eye more severe, right eye less severe, etc).
I can use sts test to test for difference in time to event between
the 2
groups (using n=24 eyes) but this does not take into account the
clustered
nature of the data.
Is there any way I can do a log-rank test which takes into account the
clustering?
You could try -stcox-, which does allow for clustering.
But the problem may run deeper than that. It could be that the status
of one eye may determine the prognosis of the other. An eye with less
severe disease may have a worse prognosis if the child's other eye
has severe disease. (This would certainly be the case in trachoma,
for instance, with the severely diseased eye acting as a nidus for
reinfection.)
And testing a more nuanced hypothesis like this using 24 eyeballs is
going to have your data stretched till they whimper.
Ron�n Conroy
[email protected]
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