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st: GLLAMM - flat or discontinuous region encountered (binary, logit)
Hello.
I am working on a case of using GLLAMM for structural equation modeling with a
binary outcome - it is a path model, with one latent variable, and I received
the message (Stata 9.2):
"
numerical derivatives are approximate
flat or discontinuous region encountered
"
===============================================================================
. gllamm fetsobrev sevar, i(nordem) family(binomial) link(logit) nocons
eq(sefac) adapt ip(g) nip(20) trace
General model information
-----------------------------------------------------------------------------
dependent variable: fetsobrev
family: binom
link: logit
denominator: 1
equation for fixed effects sevar
Random effects information for 2 level model
-----------------------------------------------------------------------------
***level 2 (nordem) equation(s):
(1 random effect(s))
standard deviation for random effect 1
nord1 : sevar
number of level 1 units = 3339
number of level 2 units = 477
Initial values for fixed effects
Iteration 0: log likelihood = -2314.4184
Iteration 1: log likelihood = -2268.9904
Iteration 2: log likelihood = -2268.9636
Logistic regression Number of obs = 3339
LR chi2(1) = .
Log likelihood = -2268.9636 Prob > chi2 = .
------------------------------------------------------------------------------
fetsobrev | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
sevar | -.5529417 .0590998 -9.36 0.000 -.6687751 -.4371083
------------------------------------------------------------------------------
start running on 10 Jan 2007 at 18:42:45
Non-adaptive log-likelihood: -2208.5065
First iteration of adaptive quadrature:
Updating posterior means and variances
log-likelihood:
-2208.5065
------------------------------------------------------------------------------
Iteration 0:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -.5529417 .5
log likelihood = -2208.5065
(not concave)
------------------------------------------------------------------------------
Iteration 1:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -3.468325 29.05551
log likelihood = -1773.4122
------------------------------------------------------------------------------
Iteration 2:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -25.39545 -74.3894
log likelihood = -1754.878
------------------------------------------------------------------------------
Iteration 3:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -55.6269 -157.9688
log likelihood = -1753.0193
------------------------------------------------------------------------------
Iteration 4:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -57.03351 -161.8858
log likelihood = -1753.0178
------------------------------------------------------------------------------
Iteration 5:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -57.7367 -163.8439
log likelihood = -1753.0171
------------------------------------------------------------------------------
Iteration 6:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.08837 -164.8232
log likelihood = -1753.0168
------------------------------------------------------------------------------
Iteration 7:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.26419 -165.3129
log likelihood = -1753.0166
------------------------------------------------------------------------------
Iteration 8:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.35211 -165.5577
log likelihood = -1753.0165
(backed up)
------------------------------------------------------------------------------
Iteration 9:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.39607 -165.6801
log likelihood = -1753.0165
(backed up)
------------------------------------------------------------------------------
Iteration 10:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.41804 -165.7413
log likelihood = -1753.0165
(backed up)
------------------------------------------------------------------------------
Iteration 11:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.42355 -165.7566
numerical derivatives are approximate
flat or discontinuous region encountered
log likelihood = -1753.0165
(backed up)
------------------------------------------------------------------------------
Iteration 12:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.47534 -165.756
numerical derivatives are approximate
flat or discontinuous region encountered
log likelihood = -1753.0163
------------------------------------------------------------------------------
(and so on until get always the same coefficients and no change in likelihood
...)
Iteration 19:
Coefficient vector:
fetsobrev: nord1:
sevar sevar
r1 -58.48807 -165.7559
numerical derivatives are approximate
flat or discontinuous region encountered
numerical derivatives are approximate
flat or discontinuous region encountered
log likelihood = -1753.0162
(backed up)
===============================================================================
I found an old message where someone with the same problem but there was a
single observation for each client and this is not my case.
Any help apreciated.
Gizelton.
FSP / USP
-----
The message I read before is available in
<http://www.stata.com/statalist/archive/2002-09/msg00456.html> :
*
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* http://www.stata.com/support/faqs/res/findit.html
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