To my knowledge, there is no built‑in function in R that exactly replicates
Stata’s expoisson. The main issue is that it can be computationally heavy since
it conditions on the sum of total counts (conditional MLE). It can only be
practical in small samples. We should be able to get similar estimates using
Firth's bias correction, for example, although I myself have not tested this
claim. The brglm2 package implements Firth's bias reduction for GLMs.
Ravi
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1. How to compute an exact Poisson model with R? (iagogv)
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Message: 1
Date: Fri, 21 Aug 2026 10:21:14 +0200
From: iagogv <[email protected]>
To: R Help <[email protected]>
Subject: [R] How to compute an exact Poisson model with R?
Message-ID: <[email protected]>
Content-Type: text/plain; charset="utf-8"
Hi all,
Can an exact Poisson regression be computed with R, instead of using the
standard (glm) Poisson using maximum likelihood?
I am working with a collegue in a project, and I'd like to reproduce his
method, if not his results. He uses Stata, particularly the expoisson
function
(https://www.stata.com/help.cgi?expoisson<https://www.stata.com/help.cgi?expoisson>)
in order to compute
the exact Poisson regression, relevant for small samples.
expoisson fits an exact Poisson regression model, which produces more
accurate inference in small samples than standard
maximum-likelihood-based Poisson regression
I know about exact Poisson tests
(https://stat.ethz.ch/R-manual/R-devel/RHOME/library/stats/html/poisson.test.html<https://stat.ethz.ch/R-manual/R-devel/RHOME/library/stats/html/poisson.test.html>),
but it does not allow to include offset.
So, is there some way to reproduce exact Poisson regression with R?
Thanks!
Best,
--
Iago
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