Totally agreed.
Nomogram (or rank table, score table) is just a nice presentation of the
model. The development and evaluation of the model is the one that matters.
In order to develop a good model, you have to know how to manipulate the
data, how to make your model better and suitable. These work can't be just
copyed from the help file in rms library.
So, take your time and follow the procedure.
1. Know R and some statistical elements
2. Read Harrell and  Steyerberg's fancy books (you should buy them) , visit
their websites.
3. Read journal articles about nomogram.


Yao Zhu
Department of Urology
Fudan University Shanghai Cancer Center
Shanghai, China


2010/3/26 Marc Schwartz <marc_schwartz@me.com>

> On Mar 25, 2010, at 9:51 AM, Frank E Harrell Jr wrote:
>
> > Marc Schwartz wrote:
> >> On Mar 25, 2010, at 8:54 AM, ЦХ wrote:
> >>> Dear volunteer:
> >>>   I am a graduate student of medcine in china.And now,I am devoting
> myself to constructing a nomograms of bladder cancer.I want to do it with
> R-project.However, I do not know how to construct a nomograms with
> R-project.I want to get yours help,thank you! I wish you can tell me the
> operating procedure of the R-project.
> >>>      And I apologize for my english,it is poor,sorry!
> >>>
>
>     truly yours
> >>>
>
>      ding ding
> >> If you are referring to a regression model based nomogram to be used for
> prediction, see the nomogram() function in the 'rms' CRAN package by Frank
> Harrell.
> >> Also, if you go to rseek.org and search using the keyword 'nomogram'
> you will find this and some other functions that provide related
> functionality.
> >> HTH,
> >> Marc Schwartz
> >
> > In addition, you will have to be expert in the type of regression
> modeling used to produce a reliable model that is then displayed in a
> nomogram.  The nomogram is the easy part; it is just a graphical display of
> a model.  It is not the model itself.
>
>
> Picking up on the important points expressed by both Frank and Ted, I would
> point you to two excellent reference texts:
>
> First, Frank's own:
>
> Regression Modeling Strategies
> Springer, 2001
>
> http://www.amazon.com/Regression-Modeling-Strategies-Frank-Harrell/dp/0387952322/
> http://biostat.mc.vanderbilt.edu/twiki/bin/view/Main/RmS
>
>
> and second:
>
> Clinical Prediction Models: A Practical Approach to Development,
> Validation, and Updating
> Ewout W. Steyerberg
> Springer, 2008
>
> http://www.amazon.com/Clinical-Prediction-Models-Development-Validation/dp/038777243X/
> http://www.clinicalpredictionmodels.org/
>
>
> HTH,
>
> Marc
>
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> and provide commented, minimal, self-contained, reproducible code.
>

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