[R] Test for multiple contrasts?

[Kaspar Pflugshaupt]

Hello,

I've fitted a parametric survival model by

> survreg(Surv(Week, Cens) ~ C(Treatment, srmod.contr), 
>    data = poll.surv.wo3)

where srmod.contr is the following matrix of contrasts:

     prep auto       poll self home
[1,]    1    1  1.0000000  0.0    0
[2,]   -1    0  0.0000000  0.0    0
[3,]    0   -1  0.0000000  0.0    0
[4,]    0    0 -0.3333333  1.0    0
[5,]    0    0 -0.3333333 -0.5    1
[6,]    0    0 -0.3333333 -0.5   -1

The summary of the model looks like this:

[snip]
                                Value Std. Error      z         p
(Intercept)                    1.4644     0.0552 26.536 3.68e-155
C(Treatment, srmod.contr)prep  0.2117     0.1268  1.669  9.50e-02
C(Treatment, srmod.contr)auto  0.1490     0.1265  1.178  2.39e-01
C(Treatment, srmod.contr)poll -0.7242     0.1639 -4.420  9.89e-06
C(Treatment, srmod.contr)self -0.2960     0.1141 -2.593  9.51e-03
C(Treatment, srmod.contr)home  0.0494     0.1068  0.462  6.44e-01
Log(scale)                    -0.4451     0.0517 -8.609  7.36e-18

[snip]

Now, I'd like to test which of my contrasts are significantly different from 
zero. I assume that the p values given by the summary are not corrected for 
multiple testing. Thus, I might correct them with p.adjust(). But since the 
contrasts are not independent, I'm not sure if the adjustment methods would 
work here.
On the other hand, I've come across a procedure called "Scheffe's multiple 
comparisons" (or S test), which is said to be appropriate for multiple 
contrasts like these. Before I try to implement it: Has anybody already done 
that, or are there good reasons not to use it?

BTW, I tried to extract the SEs of the contrasts by se.contrast(), but it 
would not work for survival models. Would they be the same that appear in the 
summary above? 

Thanks for any hints

Kaspar Pflugshaupt

-- 


Kaspar Pflugshaupt
Geobotanical Institute
ETH Zurich, Switzerland

http://www.geobot.umnw.ethz.ch
mailto:pflugshaupt at geobot.umnw.ethz.ch
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