[R] Robust regression with groups

[Dimitris Rizopoulos]

Hi Angelo,

There are two possible options (at least to my knowledge):

1. to use a random-effects model, either using `lme' (packages: nlme, 
lme4) if you have normal data or `glmmPQL' (package: MASS) or `GLMM' 
(package: lme4) or `glmmML' (package:glmmML) if you cannot use the 
normal distribution.

2. to use a gee model with a robust (sandwich) std.error estimation. 
See at `gee' (package: gee) and `geese' (package: geepack).

I hope this helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/396887
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
     http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm




----- Original Message ----- 
From: "Angelo Secchi" <secchi at sssup.it>
To: <r-help at stat.math.ethz.ch>
Sent: Wednesday, October 20, 2004 3:22 PM
Subject: [R] Robust regression with groups


>
>
> Hi,
> I have data on a group of subjects in different years. I should 
> assume
> that observations regarding different individuals are independent 
> but
> observations for the same individual in different years are not and 
> I
> would like to have an estimated standard error (and 
> variance-covariance
> matrix) taking into account this problem.
>
> More in general is there a way in R to run a (robust)regression 
> having
> different groups in the observations and specifying that the 
> observation
> are independent across groups but not necessarily independent within
> groups?
>
> Thanks
> a.
>
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