st: Problem of Monotone Likelihood in Cox Regression

[Henry <jakanyada@gmail.com>]

Dear All,
I am fitting a multivariable Cox regression model with shared frailty
to help model the within group correlation among practices since my
data is based GP prescription database.
In fitting the model, the likelihood converges to a finite estimate
(although after 45 iterations) but one of the covariates (factors)
diverges to infinity. The factor has 4 levels/groups with one of the
levels having no "failure" thus giving this infinite estimate.  This
phenomenon has been referred to by Heinze and Shemper as monotone
likelihood.
A solution to this problem in Cox regression has been implemented in
SAS and SPLUS/R
http://www.meduniwien.ac.at/msi/biometrie/publikationen/Separata/Heinze_Ploner_2002_CompMethProgBiom.pdf
I have tried to check on statlist but only managed to find a request
from Jeff n the same,
http://www.stata.com/statalist/archive/2008-02/msg00847.html.
My question is, has this been implemented in Stata? If so is it
advisable to use this in a model with shared frailty? How does this
affect the post estimation test for proportionality assumption and/or
goodness-of-fit? If this has not been implemented, can someone advise
on the way forward in this situation.
Many thanks,
Henry
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