Hi
e(chol) is the Cholesky decomposition of the variance matrix.
See below:
. matrix chol = (.97378367 , 0 \ -.86823121 , 3.586e-07)
. matrix chol2 = chol * chol'
. matrix list chol2
symmetric chol2[2,2]
r1 r2
r1 .94825464
r2 -.84546937 .75382543
Tim
"Mitchell, Michael" <[email protected]>
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25/08/2005 21:04
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st: RE: Returned results in gllamm
Greetings
I was searching for an answer to this very same question and found
Miguel's query, but no answer. I ran a random intercept, random slope
model with gllamm like this...
. eq cons : one
. eq x : x
. generate one = 1
. gllamm y x , nrf(2) eqs(x cons) i(id) link(logit) family(bin) adapt
///
nip(10)
and then got this output...
number of level 1 units = 2000
number of level 2 units = 500
Condition Number = 12.83709
gllamm model
log likelihood = -175.56749
------------------------------------------------------------------------
--
y | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------
--
x | 1.4471 .7456141 1.94 0.052 -.0142766
2.908477
_cons | 3.038546 .6268254 4.85 0.000 1.809991
4.267101
------------------------------------------------------------------------
----
Variances and covariances of random effects
-----------------------------------------------------------------------
***level 2 (id)
var(1): .94825463 (.56235789)
cov(2,1): -.84546937 (.95886005) cor(2,1): -1
var(2): .75382543 (1.5231523)
----------------------------------------------------------------------
I think I found the variance of the intercept this way...
mat list e(chol)
e(chol)[2,2]
c1 c2
r1 .97378367 0
r2 -.86823121 3.586e-07
. di .97378367 ^2
.94825464
But this does not work for the variance of the slope...
. di 3.586e-07^2
1.286e-13
Any suggestions would be greatly appreciated!
Best regards,
Michael Mitchell
UCLA ATS Statistical Consulting Group
http://www.ats.ucla.edu/stat/
> -----Original Message-----
> From: [email protected] [mailto:owner-
> [email protected]] On Behalf Of miguel foguel
> Sent: Monday, July 25, 2005 10:32 AM
> To: [email protected]
> Subject: st: Returned results in gllamm
>
> Dear all,
>
> Could anyone tell me how I can retrieve the estimated variances and
> std-errors of the random "intercepts" from an estimation using
-gllamm-?
> They don't seem to be saved in the e(V) matrix.
>
> Thank you in advance.
>
> Miguel
>
>
> *
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