[R] HOW to use the survivalROC to get optimal cut-off values?

David Winsemius dwinsemius at comcast.net
Tue Feb 21 09:21:49 CET 2012

On Feb 21, 2012, at 12:08 AM, alexiamelissa wrote:

> I have a follow up question to Dr Winsemius' post.  You can use the  
> criterion against all possible cut off values C to see which  
> minimizes the
> AIC and then that is the ideal cut off in trying to dichotomize a  
> continuous
> variable.  What I am wondering here is, does the survivalROC  
> package, or any
> other package in R or function in SAS compute this?  I have been  
> reading and
> this does not seem to be addressed anywhere so please point me in  
> the right
> direction.

The usual attempts to set a cut-point make the very restrictive and  
simplistic assumption that the cost of a decision that results in a  
false positive are the same as the cost of a false positive. This is  
almost never the case. Furthermore, these studies are often done with  
case and control populations that are not representative of the  
populations for which the test will be applied in the future. I think  
handing off the task to an automatic procedure dressed-up to construct  
and "ideal" or "scientific" answer is misguided window dressing. They  
are an effort to avoid thinking carefully about the costs of the  
alternative outcomes and fail to realize tat their are multiple  
parties being affected with no meaningful input regarding their  
respective utilities.

I'm not saying that quantitative analysis of these issues is not  
useful, just that it is unlikely to be done well by one function in a  
package in R or SAS..


David Winsemius, MD
West Hartford, CT

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