Dear R-users,

I have used the nomogram function from the rms package for a logistic
regresison model made with lrm(). Everything works perfectly (r version
2.15.1 on a mac). My question is this: if my final model is not the one
created by lrm, but I internally validated the model and 'shrunk' the
regression coefficients and computed a new intercept, how can I build a
nomogram using that object? Please see the simplified code for details:

library(rms)

x1<-rnorm(100,1,1)
x2<-rnorm(100,1,1)
y<-rbinom(100,1,0.5)

d<-data.frame(x1,x2,y)

attach(d)

ddist<-datadist(d)
options(datadist='ddist')

model<-lrm(y~x1+x2, x=TRUE, y=TRUE, data=d)
plot(nomogram(model))
##Nomogram is printed, as expected

##Now the model is internally validated, and regression coefficients are
penalized
bootstrap<-validate(model, bw=FALSE, B=100)
shrinkage<-round(bootstrap[4,5],2)
final<-round(model$coef*shrinkage, 3)
final.lp<-cbind(model$x)%*%final[-1]
final["Intercept"]<-round(lrm.fit(y=d$y, offset=final.lp)$coef,3)
final.lp<-final[1]+model$x%*%final[-1]

 ##The object 'final' now contains all model parameters, yet in a different
fashion than the lrm-created model. Does anyone have an idea how to make
this compatible again with nomogram()?

Thanks in advance for any thoughts on it.

Best wishes,
Sander

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