title: nomogram for competing risk regression
body: <p>I would like to drawing nomogram for competing risk analysis. and I Use the ordinary linear regression trick to predict the linear predictor from the competing risk regression, however, I don't know how to get the linear predictor from the crr() function. I have the following code.</p>
  
  <pre><code>  library(cmprsk)
   library(rms)
  set.seed(10)
  ftime &lt;- rexp(200)
  fstatus &lt;- sample(0:2,200,replace=TRUE)
  cov &lt;- matrix(runif(600),nrow=200)
  dimnames(cov)[[2]] &lt;- c('x1','x2','x3')
  z &lt;- crr(ftime,fstatus,cov)
  z.p &lt;- predict(z,cov)
  n=60#suppose I want to predict the probability of event at time 60(an order)
  df&lt;-data.frame(y=z.p[n,-1],cov)
  ddist &lt;- datadist(df)  
  options(datadist='ddist') 
  lmod&lt;-ols(y~rcs(x1)+rcs(x2)+rcs(x3),data=df)#y is not linear predictor of crr fitting, this ols modeling can be wrong. the R^2 will not be 1. 
  nom&lt;-nomogram(lmod)
  plot(nom,lplabel=paste("prob. of incidence T",round(z.p[n,1],2),sep="="))
  </code></pre>