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# st: Fwd: xtmelogit predict generates missing values

 From Rachel Cole To statalist Subject st: Fwd: xtmelogit predict generates missing values Date Tue, 2 Jul 2013 09:18:42 +0530

```Hi there,
I'm using xtmelogit and predict (reffects, mu, and deviance) with a
dataset with no missing values.  In a couple of instances when I use
predict, Stata informs me that it is generating missing values--an
example is below.  In this example I have 2248 observations nested in
135 schools (schid) and bsttrn is an indicator variable that equals 1
for 14%.
xtmelogit bsttrn || schid:
Refining starting values:

Iteration 0:   log likelihood = -575.44982
Iteration 1:   log likelihood =  -476.2408
Iteration 2:   log likelihood = -463.97972

Iteration 0:   log likelihood = -463.97972
Iteration 1:   log likelihood = -450.95784
Iteration 2:   log likelihood = -446.10531
Iteration 3:   log likelihood =  -446.0206
Iteration 4:   log likelihood = -446.01967
Iteration 5:   log likelihood = -446.01966

Mixed-effects logistic regression               Number of obs      =      2248
Group variable: schid                           Number of groups   =       136

Obs per group: min =         1
avg =      16.5
max =        40

Integration points =   7                        Wald chi2(0)       =         .
Log likelihood = -446.01966                     Prob > chi2        =         .

------------------------------------------------------------------------------
bsttrn |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
_cons |  -7.026729   1.224348    -5.74   0.000    -9.426407   -4.627051
------------------------------------------------------------------------------

------------------------------------------------------------------------------
Random-effects Parameters  |   Estimate   Std. Err.     [95% Conf. Interval]
-----------------------------+------------------------------------------------
schid: Identity              |
sd(_cons) |   4.311155   .6488151      3.209893    5.790243
------------------------------------------------------------------------------
LR test vs. logistic regression: chibar2(01) =   962.05 Prob>=chibar2 = 0.0000

. predict re1_cons, reffects
(557 missing values generated)
Predictions are only made for schools with 0% bsttrn or a very few
(less than 5%).  No predictions are made for schools with some
variation in bsttrn or 100% bsttrn.

So, besides missing data, under what circumstances would xtmelogit's
predict produce missing values? In this example, what causes the
missing values for schools with variation in bsttrn?