[R] mantelhaen.test for more than two groups?

[Francisco J. Zagmutt]

How about using logistic regression?  When you have K dimensional tables and 
several potential confounders it might be better to go for a multivariable 
model. Take a look at function glm(stats) and lrm(Design).

Cheers

Francisco

>From: Peter Dalgaard <p.dalgaard at biostat.ku.dk>
>To: Thomas Lumley <tlumley at u.washington.edu>
>CC: Katrin Schweitzer <Katrin.Schweitzer at ims.uni-stuttgart.de>,        
>r-help at stat.math.ethz.ch
>Subject: Re: [R] mantelhaen.test for more than two groups?
>Date: 26 Apr 2005 18:24:31 +0200
>
>Thomas Lumley <tlumley at u.washington.edu> writes:
>
> > On Tue, 26 Apr 2005, Katrin Schweitzer wrote:
> >
> > > Dear All,
> > >
> > > I'd like to perform the generalized Cochran-Mantel-Haenszel-Test (as
> > > described in Agresti (1990), Categorical Data Analysis) for my
> > > nominal data.
> > >
> > > My problem is that I have more than two groups. In fact I think I'd
> > > need an 5-dimensional array for the response variable, the control
> > > variable and three group variables.
> > > Could you please tell me if this is possible in R - and if yes how I
> > > am supposed to do this?
> >
> > You're supposed to have a three-dimensional array: exposure x response
> > x group.
> >
> > This means turning your three group variables into one variable.  One
> > way to do this is with the interaction() function.
>
>Or, if data are already counts, change the dimensions (as in dim(x) <-
>c(2,3,8)), possibly after using aperm() to get the indices in the
>right order.
>
>--
>    O__  ---- Peter Dalgaard             Blegdamsvej 3
>   c/ /'_ --- Dept. of Biostatistics     2200 Cph. N
>  (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
>~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907
>
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