[R] Preferable contrasts?

Frank E Harrell Jr fharrell at virginia.edu
Thu Nov 7 17:23:32 CET 2002


On Thu, 7 Nov 2002 10:36:50 +0100 
"Grathwohl,Dominik,LAUSANNE,NRC/NT" <dominik.grathwohl at rdls.nestle.com> wrote:

> Dear all,
> 
> I'm working with Cox-regression, because data could be censored. 
> But in this particular case not. 
> Now I have a simple example: PRO and PRE are (0,1) coded.
> The response is not normal distributed. 
> We are interested in a model which could describe interaction.
> But my results are depending strongly in the choose of the contrast option.
> It is clear that there is some dependence in the contrasts, but in this
> simple case 
> I could get the vice versa effect.
> My R output:
> 
> > options(contrasts = c(unordered = "contr.treatment", ordered =
> "contr.poly"))
> > summary(coxph(Surv(ILOG, alive) ~ factor(PRO)*factor(PRE)))
> ...
>                              coef exp(coef) se(coef)      z     p
> factor(PRO)1               0.6576     1.930    0.302  2.177 0.029
> factor(PRE)1               0.0681     1.070    0.304  0.224 0.820
> factor(PRO)1:factor(PRE)1 -0.7703     0.463    0.431 -1.789 0.074
> ...
> > options(contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
> > summary(coxph(Surv(ILOG, alive) ~ factor(PRO)*factor(PRE)))
> ...
>                             coef exp(coef) se(coef)      z     p
> factor(PRO)0               0.113     1.119    0.304  0.370 0.710
> factor(PRE)0               0.702     2.018    0.299  2.350 0.019
> factor(PRO)0:factor(PRE)0 -0.770     0.463    0.431 -1.789 0.074
> ...
> 
> What would the experts recommend?
> 
> Kind regards,
> 
> Dominik
> 
> Dominik Grathwohl 
> Biostatistician 
> Nestlé Research Center 
> PO Box 44, CH-1000 Lausanne 26 
> Phone: + 41 21 785 8034 
> Fax: + 41 21 785 8556 
> e-mail: dominik.grathwohl at rdls.nestle.com 

Think of what you want to estimate.  I like to think of differences in predicted values (or the anti-log of such differences, i.e., hazard ratios).  To make estimates independent of all coding decisions I wrote contrast.Design for the Design library.  Here is an example:

library(Design)   # from http://hesweb1.med.virginia.edu/biostat/s/Design.html
f <- cph(Surv(dtime,event) ~ PRO*PRE)  
# make PRO and PRE factors in the data frame
contrast(f, list(PRO='somevalue',PRE='somevalue'),
            list(PRO='someothervalue',PRE='someothervalue'))

The contrast compares predicted values for the two pairs of settings of (PRE,PRO).

Frank
-- 
Frank E Harrell Jr              Prof. of Biostatistics & Statistics
Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences
U. Virginia School of Medicine  http://hesweb1.med.virginia.edu/biostat
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