<>
The ci returned by -nlcom- is off slightly, I do not know why, though.
On the occasion of this thread: -coeflegend- with -xtmelogit- should ideally
include the random effects parameters as well, because this is where the
biggest difficulties with the correct syntax are encountered, as seems to be
the case for Doug as well.
I would also argue that the syntax elements returned by -coeflegend- calls
should be clickable, just like the variables in the variables window, so
users can conveniently insert the elements into the command window.
*************
webuse bangladesh, clear
/*Random-intercept model,
analogous to xtlogit */
xtmelogit c_use urban/*
*/ age child* || district:
nlcom (sd: exp(_b[lns1_1_1:_cons]))
xtmelogit, coefle
*************
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Martin Weiss
Sent: Mittwoch, 11. November 2009 22:43
To: [email protected]
Subject: RE: st: Intraclass correlation and binary hierarchical models
<>
*************
webuse bangladesh, clear
/*Random-intercept model,
analogous to xtlogit */
xtmelogit c_use urban/*
*/ age child* || district:
nlcom (sd: exp(_b[lns1_1_1:_cons]))
*************
HTH
Martin
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Levy, Douglas E.,
Ph.D.
Sent: Mittwoch, 11. November 2009 22:34
To: [email protected]
Subject: RE: st: Intraclass correlation and binary hierarchical models
Thanks, all, for your responses.
Nevertheless, I'm still wondering if anyone is aware of how to extract or
calculate something equivalent to xtlogit's sigma_u in xtmelogit? And how
does
one get from the ereturn values in xtmelogit to the variance (or std.
deviation)
estimates listed in the random effects table?
Best,
Doug
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of
[email protected]
Sent: Wednesday, November 11, 2009 3:45 PM
To: [email protected]
Subject: Re: st: Intraclass correlation and binary hierarchical models
Though not a direct answer to your question, you might find the
following pertinent:
Comparing the contributions of groups of predictors: which outcomes
vary with hospital rather than patient characteristics? Journal of the
American Statistical Association, March, 1995 by Rosenbaum, Paul R.;
Ross, Richard N.; Silber, Jeffrey H.
Abstract: Death, adverse occurence and failure are considered as
patient outcomes and compared across hospitals. The effects generated
by differences in patient cases and hospital administration are
removed to determine the quality of care level. Logit models are
compared to examine the impact of patient and hospital
characteristics. It is shown that outcome variations are conditioned
more by patient characteristics.
-Steve
Steve Samuels
[email protected]
18 Cantine's Island
Saugerties NY 12477
USA
845-246-0774
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