[R] changes in coxph in "survival" from older version?

[Frank Harrell]

Please don't be serious about doing variable selection with this dataset.
Frank

Shi, Tao wrote:
> 
> Hi Terry,
> 
> Really appreciate your help!  Sorry for my late reply.
> 
> I did realize that there are way more predictors in the model.  My initial 
> thinking was use that as an initial model for stepwise model selection. 
> Now I 
> wonder if the model selection result is still valid if the initial model
> didn't 
> even converge?
> 
> Thanks!
> 
> ...Tao
> 
> 
> 
> 
> ----- Original Message ----
>> From: Terry Therneau <therneau at mayo.edu>
>> To: "Shi, Tao" <shidaxia at yahoo.com>
>> Cc: r-help at r-project.org
>> Sent: Thu, May 12, 2011 6:42:09 AM
>> Subject: Re: changes in coxph in "survival" from older version?
>> 
>> 
>> On Wed, 2011-05-11 at 16:11 -0700, Shi, Tao wrote:
>> > Hi all,
>> > 
>> > I found that the two different versions of "survival" packages, namely  
>>2.36-5 
>>
>> > vs. 2.36-8 or later, give different results for coxph  function. 
>> Please see 
> 
>> > below and the data is attached.  The  second one was done on Linux, but 
>>Windows 
>>
>> > gave the same results.   Could you please let me know which one I
>> should 
>>trust?
>> > 
>> >  Thanks,
>> 
>>  In your case, neither.  Your data set has 22 events and 17  predictors;
>> the rule of thumb for a reliable Cox model is 10-20 events per  predictor
>> which implies no more than 2 for your data set.  As a result,  the
>> coefficients of your model have very wide confidence intervals, the  coef
>> for Male for instance has se of 3.26, meaning the CI goes from 1/26  to
>> 26 times the estimate; i.e., there is no biological meaning to  the
>> estimate.
>> 
>>   Nevertheless, why did coxph give a different  answer?  The later
>> version 2.36-9 failed to converge (20 iterations)  with a final
>> log-likelihood of -19.94, the earlier code converges in 10  iterations to
>> -19.91.  In version 2.36-6 an extra check was put into the  maximizer for
>> coxph in response to an exceptional data set which caused the  routine to
>> fail due to overflow of the exp function; the Newton-Raphson  iteration
>> algorithm had made a terrible guess in it's iteration path, which  can
>> happen with all NR based search methods.  
>>    I put a limit  on the size the linear predictor in the Cox model of
>> 21.  The basic  argument is that exp(linear-predictor) = relative risk
>> for a subject, and  that there is not much biological meaning for risks
>> to be less than exp(-21)  ~ 1/(population of the earh).  There is more to
>> the reasoning,  interested parties should look at the comments in
>> src/coxsafe.c, a 5 line  routine with 25 lines of discussion.  I will
>> happily accept input the  "best" value for the constant.
>> 
>>    I never expected to see a data set  with both convergence of the LL
>> and linear predictors larger than +-15.   Looking at the fit (older code)
>> > round(fit2$linear.predictor, 2)
>>   [1]   2.26   0.89   4.96 -19.09 -12.10   1.39    2.82   3.10
>>  [9]  18.57 -25.25  22.94   8.75   5.52  -27.64  14.88 -23.41
>> [17]  13.70 -28.45  -1.84   10.04  12.62   2.54   6.33  -8.76
>> [25]   9.68    4.39   2.92   3.51   6.02 -17.24   5.97
>> 
>> This says  that, if the model is to be believed, you have several near
>> immortals in the  data set. (Everyone else on earth will perish first).
>> 
>> Terry  Therneau
>> 
>> 
>> 
>>
> 
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 


-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
View this message in context: http://r.789695.n4.nabble.com/changes-in-coxph-in-survival-from-older-version-tp3516101p3527017.html
Sent from the R help mailing list archive at Nabble.com.