Many thanks for the prompt response.

However, I am afraid that it is not completely clear for me. I

apologize, I am not a statistician.

Sorry, may be what I will say make totally non sense, but what I

understood is the following:

Let's suppose that I need to predict cancer-specific survival using

the variables X and Y. What I need to do is to develop a model that

include these variables and predict cancer-specific survival using the

competing-risks regression. Then, I shall calculate the "predictions"

of this model at a certain time point, then I shall use these

prediction as an "endpoint", and predict it using a linear regression

model that include the same variables, i.e X and Y. Finally, I use the

coefficients of this final model to develop a nomogram. Is that

correct?

Many thanks again

Should I calculate the "prediction" of the competing-risks regression

model, and then use this "prediction" as an "endpoint" and predict it

using a linear regression by including the same variables as

predictors?

On Fri, Jun 24, 2011 at 1:27 PM, Frank Harrell [via R]

<

[hidden email]> wrote:

> Replace the Design package with the rms package. Use the ordinary linear

> regression trick to predict the linear predictor from the competing risk

> regression, then use nomogram on this new model (that merely represents the

> fit of interest).

> Frank

>

> Firas Abdollah wrote:

> Hi R users,

>

> I'd like to draw a nomogram using a competing-risks regression (crr function

> in R), rather than a cox regression. However, the nomogram function provided

> in the Design package is not good for this purpose.

> Do you have any suggestion.

> I really appreciate your help

>

> Many thanks

>

> F.Abdollah, MD

> San-Raffele hospital

> Milan, Italy

>

> Frank Harrell

> Department of Biostatistics, Vanderbilt University

>

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--

Firas Abdollah, MD

Dept. of Urology

San Raffaele Hospital

Vita-Salute University,

Via Olgettina 60, 20132, Milan, Italy

Tel. +39 02 2643 7286

Fax. +39 02 2643 7298

E-mail:

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