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HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Levy, Douglas E.,
Ph.D.
Sent: Mittwoch, 11. November 2009 21:07
To: [email protected]
Subject: st: Intraclass correlation and binary hierarchical models
Hi All,
This is partly a stats question, partly a Stata question. I have binary
outcome
data and I'm interested in calculating intraclass correlation for a
multilevel/hierarchical model that is nested as follows: patients within
hospitals within regions. I want to know what proportion of the variance in
outcomes resides at each level of hierarchy to help direct quality control
efforts.
If my data were linear, I could run:
xtmixed Y || region: || hospital:, variance
I would add up the region, hospital, and residual variances, and see what
fraction of the total variance resided at each level.
If I had binary data and only had two levels of hierarchy, say hospital and
patient, I could run xtlogit:
xtlogit Y, re i(hospital)
and the rho statistic would be my estimate of intraclass correlation (am I
correct here?).
The "correct" model to run with my binary outcome data would be:
xtmelogit Y || region: || hospital:, variance
but this only reports the variance for region and hospital. There is no
residual
variance reported to estimate the total variance (which I suppose makes
sense
with binary data), and Stata does not report a level-specific rho as it does
with xtlogit.
I'd be grateful for the group's thoughts on how to tackle this issue
statistically and/or with respect to Stata.
Best,
Doug
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