On 05/19/2010 03:17 PM, Marc Carpentier wrote:
Dear list, I'm facing the following problem : A cox model with my sex
variable interacting with several continuous variables :
cph(S~sex*(x1+x2+x3)) And I'd like to make a nomogram. I know it's a
bit tricky and one mights argue that nomogram is not a good a
choice... I could use the parameter
interact=list(sex=("male","female"),x1=c(a,b,c))... but with rcs or
pol transformations of x1, x2 and x3, the choice of the
categorization (a,b,c,...) is arbitrary and the nomogram not so
useful... Considering that sex is the problem, I thought I could draw
two nomograms, one for each sex... based on one model. These would be
great. Do you think it's possible ?

Yes, you can specify constant predictors not to draw with the omit= argument. But try first to draw everything. Shouldn't you just get 2 axes each for x1 x2 x3?


Taking the exemple of the help of nomogram() (package "rms") : f<-
psm(Surv(d.time,death) ~ sex*age, dist=if(.R.)'lognormal' else
'gaussian')

Drop the if(.R.) which was just corrected in the documentation. Use dist='lognormal'

Frank


Let's add the previously defined blood.pressure effect with an
interaction with sex too (with cph) : f2<- cph(Surv(d.time,death) ~
sex*(age+blood.pressure))

I thought of the parameter adt.to : plot(nomorgam(f2,
adj.to=list(sex="male")) #and "female" for the other one

But nomogram() still wants me to define interact=list(...) Thanks for
any advice you might have (with adj.to or any alternative...)

Marc Carpentier



--
Frank E Harrell Jr   Professor and Chairman        School of Medicine
                     Department of Biostatistics   Vanderbilt University

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