[R] Robust standard errors in logistic regression

Martin Maechler maechler at stat.math.ethz.ch
Wed Jul 5 10:25:59 CEST 2006


>>>>> "Celso" == Celso Barros <celso.barros at 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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