st: glm error message after binomial log or identity link models withmissing data

[Jane Schroeder <Jane_Schroeder@unc.edu>]

When I run binomial -glm- models with a log or identity link function I 
get the following error message whenever there are observations with 
missing data for a model covariate, even though all predicted risks are 
well within the permissible (0,1) range:

Warning: parameter estimates produce inadmissible mean estimates in one 
or more observations.

For example, when I fit a linear risk model to the following (no missing 
data), I don't get the error message:

 20-36 vs. |    child's gender
 37+ weeks |    female       male |     Total
-----------+----------------------+----------
      term |    29,059     30,116 |    59,175
   preterm |     3,591      4,218 |     7,809
-----------+----------------------+----------
     Total |    32,650     34,334 |    66,984

. glm preterm sex, fam(bin) link(ident)

------------------------------------------------------------------------------
             |                 OIM
     preterm |      Coef.   Std. Err.      z    P>|z|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
         sex |   .0128673   .0024772     5.19   0.000      .008012 
.0177226
       _cons |   .1099847   .0017315    63.52   0.000      .106591 
.1133784
------------------------------------------------------------------------------
Coefficients are the risk differences

However, if I recode one observation to missing for 'sex' and rerun the 
model I get the error message, e.g.:

replace sex=. in 1
(1 real change made, 1 to missing)

. glm preterm sex, fam(bin) link(ident)

------------------------------------------------------------------------------
             |                 OIM
     preterm |      Coef.   Std. Err.      z    P>|z|     [95% Conf. 
Interval]
-------------+----------------------------------------------------------------
         sex |   .0128709   .0024773     5.20   0.000     .0080155 
.0177262
       _cons |   .1099847   .0017315    63.52   0.000      .106591 
.1133784
------------------------------------------------------------------------------
Coefficients are the risk differences
Warning: parameter estimates produce inadmissible mean estimates in one 
or more observations.

Note that the predicted risk for a female (.1099847) is unchanged from 
the previous model, and the predicted risk for a male (with one preterm 
observation missing) is essentially unchanged (.1228556 vs. .122852).

It's not that much trouble to generate and review the predicted risks 
after every model, but I hate to get into the habit of ignoring error 
messages. Any suggestions? Thanks-

Jane Schroeder


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