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Re: st: glm error message after binomial log or identity link models with missing data


From   Maarten buis <maartenbuis@yahoo.co.uk>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: glm error message after binomial log or identity link models with missing data
Date   Mon, 18 Feb 2008 21:11:05 +0000 (GMT)

I think that StataCorp forgot an -if e(sample)- in the -CheckAdmiss-
sub-program of -glm- (you can see that when you type -viewsource
glm.ado-) and counted missing values as violations.

You can check the predictions yourself by typing after your -glm-
model:
predict mu
assert mu >= 0 & mu <= 1 if e(sample)

Hope this helps,
Maarten

--- Jane Schroeder <Jane_Schroeder@unc.edu> wrote:

> 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
> 
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/support/faqs/res/findit.html
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
> 


-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434

+31 20 5986715

http://home.fsw.vu.nl/m.buis/
-----------------------------------------


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*
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