Re: [R] Robust standard errors in logistic regression

From: Martin Maechler <maechler_at_stat.math.ethz.ch>
Date: Wed 05 Jul 2006 - 18:25:59 EST

>>>>> "Celso" == Celso Barros <celso.barros@gmail.com>
>>>>> on Wed, 5 Jul 2006 04:50:29 -0300 writes:

 [...............]

    Celso> By the way, I was wondering if there is a way to use rlm (from MASS)     Celso> to estimate robust standard errors for logistic regression?

rlm stands for 'robust lm'. What you need here is 'robust glm'.

I've already replied to a similar message by you, mentioning the (relatively) new package "robustbase". After installing it, you can
use

        robustbase::glmrob()

[or just glmrob(), after attaching the package by "library(robustbase)"] and its summary function does provide you with robust standard errors (and even P-values which you seem to like particularly ;-).

Martin Maechler, ETH Zurich



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