I'm sorry. I don't understand the "omit" solution, and maybe I mislead you with my explanation.
With the data from the "f" exemple of nomogram() : Let's declare : f2 <- cph(Surv(d.time,death) ~ sex*(age+blood.pressure)) I guess the best (and maybe the only) way to represent it with a nomogram is to plot two nomograms (I couldn't find better). Is there a way to have : Nomogram1 : "male" : - points 1-100 --------------- - age ("men") --------------- - blood.pressure ("men") --------------- - linear predictor --------------- And nomogram2 : "female" : - points 1-100 --------------- - age ("female") --------------- - blood.pressure ("female") --------------- - linear predictor --------------- As I said I tried and failed (nomogram() still wants me to define interact=list(...)) with : plot(nomorgam(f2, adj.to=list(sex="male")) #and "female" for the other one Marc ----- Message d'origine ---- De : Frank E Harrell Jr <f.harr...@vanderbilt.edu> À : Marc Carpentier <marc.carpent...@ymail.com>; r-help-request Mailing List <r-help@r-project.org> Envoyé le : Mer 19 mai 2010, 22h 28min 51s Objet : Re: [R] Nomogram with multiple interactions (package rms) 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.