R help - May 2008 - Negative Binomial Model

Hello,

I am trying to run a negative binomial regression model in R and can't get
the
standard errors to match the output I get from the Stata nbreg command. I've
tried a few different options but haven't had much luck. The closest
I've
found
is:

gamlss(formula, family = NBI, sigma.formula = ~ 1,data=dataframe)

...But this is still a little off most of the time and pretty far off at
other
times (compared with the Stata output). The glm.nb from the MASS package
produces the correct coefficients, but different (usually very different)
standard errors.

Could anybody explain this and point me in the right direction? I'd really
appreciate it.

Thank you,

Mike Ryckman
Department of Political Science
University of Arizona

On Wed, 14 May 2008, Mike Ryckman wrote:
> Hello,
>
> I am trying to run a negative binomial regression model in R and can't
get
> the
> standard errors to match the output I get from the Stata nbreg command.
I've
> tried a few different options but haven't had much luck. The closest
I've
> found
> is:
>
> gamlss(formula, family = NBI, sigma.formula = ~ 1,data=dataframe)
>
> ...But this is still a little off most of the time and pretty far off at
> other
> times (compared with the Stata output). The glm.nb from the MASS package
> produces the correct coefficients, but different (usually very different)
> standard errors.
>
> Could anybody explain this and point me in the right direction? I'd
really
> appreciate it.
Well, you don't really give us enough information to know (a reproducible 
R example and the desired standard errors from Stata would have been 
helpful). My guess is that Stata uses some sort of "robust" standard 
errors, i.e., sandwich standard errors. Try something like:
   library("MASS")
   library("sandwich")
   library("lmtest")
   fm <- glm.nb(...)
   coeftest(fm, vcov = sandwich)

See also the following thread for some more discussion for count data 
regression in R and Stata:
   https://stat.ethz.ch/pipermail/r-help/2008-May/161640.html

hth,
Z
> Thank you,
>
> Mike Ryckman
> Department of Political Science
> University of Arizona
>
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