GAMLj3 - robust standard errors for poisson regression

[diogohcc]

Dear colleagues.

Is the function for estimate robust standard errors not available for poisson regression? In the module GAMLj3, the option of robust standard errors is available only for General Linear models, but not for generalized linear model.

Best regards.

[mcfanda@gmail.com]

At present, they are not implemented. Nevertheless, what would be the theoretical rationale for employing robust standard errors in generalized linear models? In standard GLMs, robust estimators are typically used to correct for heteroscedasticity or related violations of model assumptions; however, heteroscedasticity is not an assumption of generalized linear models. If one wishes to move beyond standard errors based on model assumptions, a bootstrap confidence interval may be preferable, as it can provide insights into the stability of the estimates without relying on specific distributional assumptions.

[diogohcc]

Thank you very much for your reply.
I agree with the comments.
However, Poisson regression with robust standard error is a way to estimate the prevalence ratio for highly prevalent dichotomous outcomes (in this case do not assume Poisson distribution). It provides a better estimate compared to logistic regression, as well as in cases where negative log-binomial regression present problems of convergence. Robust adjustment for Poisson regression is available in STATA, but I have chosen to use jamovi because I appreciate the project. However, in this case, the absence of robust standard error prevent to use jamovi.

Best regards.