[R] results of a survival analysis change when converting the data to counting process format

[Göran Broström]

Den 2019-08-22 kl. 21:48, skrev Göran Broström:
> 
> 
> On 2019-08-18 19:10, Ferenci Tamas wrote:
>> Dear All,
>>
>> Consider the following simple example:
>>
>> library( survival )
>> data( veteran )
>>
>> coef( coxph(Surv(time, status) ~ trt + prior + karno, data = veteran) )
>>           trt        prior        karno
>>   0.180197194 -0.005550919 -0.033771018
>>
>> Note that we have neither time-dependent covariates, nor time-varying
>> coefficients, so the results should be the same if we change to
>> counting process format, no matter where we cut the times.
>>
>> That's true if we cut at event times:
>>
>> veteran2 <- survSplit( Surv(time, status) ~ trt + prior + karno,
>>                         data = veteran, cut = unique( veteran$time ) )
>>
>> coef( coxph(Surv(tstart,time, status) ~ trt + prior + karno, data = 
>> veteran2 ) )
>>           trt        prior        karno
>>   0.180197194 -0.005550919 -0.033771018
>>
>> But quite interestingly not true, if we cut at every day:
>>
>> veteran3 <- survSplit( Surv(time, status) ~ trt + prior + karno,
>>                         data = veteran, cut = 1:max(veteran$time) )
>>
>> coef( coxph(Surv(tstart,time, status) ~ trt + prior + karno, data = 
>> veteran3 ) )
>>           trt        prior        karno
>>   0.180197215 -0.005550913 -0.033771016
>>
>> The difference is not large, but definitely more than just a rounding
>> error, or something like that.
>>
>> What's going on? How can the results get wrong, especially by
>> including more cutpoints?
> 
> All results are wrong, but they are useful (paraphrasing George EP Box).

That said, it is a little surprising: The generated risk sets are 
(should be) identical in all cases, and one would expect rounding errors 
to be the same. But data get stored differently, and ... who knows?

I tried your examples on my computer and got exactly the same results as 
you. Which surprised me.

G,

> 
> Göran
> 
>>
>> Thank you in advance,
>> Tamas
>>
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> 
> ______________________________________________
> R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.