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Re: st: Cox Regression - flat region resulting in a missing likelihood


From   Theresa Maria Andorfer <andorfer.tm@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Cox Regression - flat region resulting in a missing likelihood
Date   Tue, 30 Apr 2013 15:38:13 +0200

Thank you for the ton of advice,

Best Theresa
On Apr 30, 2013, at 3:25 AM, graupel75@gmail.com wrote:

> One other option is a convergence trick from 'Methods for estimating
> adjusted risk ratios' by Peter Cummings, The Stata Journal (2009) 9,
> Number 2, pp. 175–196.
> 
> http://www.stata-journal.com/sjpdf.html?articlenum=st0162
> 
> It's the last paragraph on pg 180.
> 
> On Tue, Apr 30, 2013 at 8:04 AM,  <graupel75@gmail.com> wrote:
>> Theresa writes:
>> 
>>> I set my data stset and then I tried to run a stcox and got the following
>>> error message " flat region resulting in a missing likelihood r(430)";
>> 
>> I would first try to change the settings for ties (Efron, exactp,
>> exactm) if you have many tied failure times.
>> 
>> Beyond that, it likely due to so-called 'mono-tone' likelihood;
>> there's a solution called the Firth method. Unfortunately, it is not
>> implemented in Stata for Cox models (but is in Some Alternative
>> Software and in R).
>> 
>> You could also try to randomize your times slightly (which likely
>> won't work); use flexible parametric models which will require some
>> startup (-ssc install stpm2-); or do a Poisson regression to get
>> (essentially) the same coefficients as Incident Rate Ratios instead of
>> HRs. Best source of how to do this is Dupont's 'Statistical Modeling
>> for Biomedical Researchers'.
>> 
>> cheers-
>> Andrew Lover
>> ______________________________________________
>> Epidemiologist
>> Centre for Infectious Disease Epidemiology Research (CIDER)
>> Saw Swee Hock School of Public Health
>> National University of Singapore
> 
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