A Modified Poisson Regression - Zhou et al Approach in R-INLA

[Prince Michael Amegbor]

Hi everyone,

I'm exploring the implementation of a modified Poisson regression with robust variance, following the recommendation by Zhou et al. in 2004. This is particularly useful for modeling a binary outcome with a common prevalence ratio (PR).

In R, you can achieve this using the glm model and the sandwich package for robust variance. Here's an example:

library("sandwich")
library("lmtest")

model <- glm(outcome ~ exposure, family = poisson(link = log), data = dataset)
coeftest(model, vcov = sandwich)

This model, expressed as log(λ) = β₀ + β₁ ⋅ exposure, calculates standard errors with robust variance for more reliable results.

SErobust​(βi​)=V(βi​)√​

I'm curious if there's a way to implement this approach in the r-inla.
 

[Helpdesk (Haavard Rue)]

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Håvard Rue
he...@r-inla.org