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help for ^rglm^                                    (STB-50: sg114)
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Generalized linear models with robust variance estimates
--------------------------------------------------------

	^rglm^  [varlist] [weight] [^if^ exp] [^in^ range]
                [^,^  ^cl^uster^(^varname^)^ ^ms^pec ^td^ist ^mi^nus^(^#^)^
                glm-options ]

Description
-----------

^rglm^ fits generalized linear models and calculates a Huber (sandwich)
estimate of the variance-covariance matrix of estimates. It can be used 
alone or called without arguments after a previous call to ^glm^. As
with other  "robust" commands, the units may be considered to fall into
clusters.


Options for use with ^rglm^
-------------------------

^cluster(^varname^)^ specifies the variable which defines sampling
clusters.

^mspec^ specifies that full Huber variances be used. These are robust to
mis-specification of conditional means. If ^mspec^ is absent, semi-Huber
variances are calculated, robust to variance mis-specification caused by
overdispersion, underdispersion, heteroscedasticity and clustering,
but assuming that conditional means are specified correctly by the model.
(Except in the case of canonical link functions, where the semi-Huber
variance is the full Huber variance. See Section 2.5 of McCullagh and
Nelder (1989).)

^tdist^ specifies that P-values and confidence intervals are to be
calculated assuming estimates to have a t-distribution with M-p
degrees of freedom, where p is the number of model parameters, and M is
the number of clusters if ^cluster^ is specified, or the number of
observations if ^cluster^ is not specified.

^minus(^#^)^ specifies the ^minus^ parameter to pass to ^_robust^, to
apply a finite-sample adjustment to the Huber covariance matrix. If
absent (or negative), it is reset to p (the number of model parameters).

If a varlist is supplied, then all ^glm^ options are allowed. If not,
then the only ^glm^ options allowed are ^level^ and ^eform^, and
^cluster^, ^mspec^, ^tdist^ and ^minus^ are ignored.


Examples
--------

 . ^glm dead ln_dose, family(binomial ntest) link(logit)^
 . ^rglm, ms^

 . ^rglm dead ln_dose, family(binomial ntest) link(logit)^

 . ^rglm dead ln_dose, family(binomial ntest) link(logit) clust(group)^


Author
------

      Roger Newson
      Imperial College School of Medicine
      London, UK
      r.newson@@ic.ac.uk


Acknowledgment
--------------

This program was based on a previous version called hglm, which
calculated only semi-Huber variances, and was kindly supplied to the
author by David Clayton of MRC in Cambridge, England.


References
----------

McCullagh, P. and J. A. Nelder. 1989. Generalized Linear Models. 2d ed.
London: Chapman & Hall.


Also see
--------

    STB:  STB-50 sg114
 Manual:  [R] glm, [R] _robust