[R] Repeated measures Cox regression ??coxph??

[Göran Broström]

On 07/26/2013 04:06 AM, John Sorkin wrote:
> David Thank you for your thoughts. The data I am analyzing do not
> come from a clinical trial but rather from a cohort study whose aim
> is to determine risk factors for surgical therapy to treat their
> joints. John

As David explained, there are several ways of approaching this 
situation. If it is a treatment/control case (which yours isn't), 
stratification is appropriate. It boils down to a simple sign test 
where we compare the number of pairs with longest survival of the 
treated with the number of pairs with the longest survival of the 
control. Undetermined (due to censoring) pairs are thrown away.

Generally, stratification is an alternative to the frailty model, but it 
has some drawbacks: loss of power (especially with small stratum sizes), 
and you cannot use covariates that are constant within pairs (personal 
characteristics in your case). The frailty model comes with stronger 
assumptions than stratification, but you avoid the drawbacks just 
mentioned. The clustering method, finally, is for variance correction in 
the ordinary Cox regression.

In your case, would recommend the frailty approach with coxme (while we 
wait for Terry's verdict!).

Göran

> Sent from my iPhone
>
> On Jul 25, 2013, at 9:15 PM, "Marc Schwartz <marc_schwartz at me.com>"
> <marc_schwartz at me.com> wrote:
>
>>
>> On Jul 25, 2013, at 4:45 PM, David Winsemius
>> <dwinsemius at comcast.net> wrote:
>>
>>>
>>> On Jul 25, 2013, at 12:27 PM, Marc Schwartz wrote:
>>>
>>>>
>>>> On Jul 25, 2013, at 2:11 PM, John Sorkin
>>>> <jsorkin at grecc.umaryland.edu> wrote:
>>>>
>>>>> Colleagues, Is there any R package that will allow one to
>>>>> perform a repeated measures Cox Proportional Hazards
>>>>> regression? I don't think coxph is set up to handle this type
>>>>> of problem, but I would be happy to know that I am not
>>>>> correct. I am doing a study of time to hip joint replacement.
>>>>> As each person has two hips, a given person can appear in the
>>>>> dataset twice, once for the left hip and once for the right
>>>>> hip, and I need to account for the correlation of data from a
>>>>> single individual. Thank you, John
>>>>
>>>>
>>>>
>>>> John,
>>>>
>>>> See Terry's 'coxme' package:
>>>>
>>>> http://cran.r-project.org/web/packages/coxme/index.html
>>>
>>> When I looked over the description of coxme, I was concerned it
>>> was not really designed with this in mind. Looking at Therneau
>>> and Grambsch, I thought section 8.4.2 in the 'Multiple Events per
>>> Subject' Chapter fit the analysis question well. There they
>>> compared the use of coxph( ...+cluster(ID),,...)  withcoxph(
>>> ...+strata(ID),,...). Unfortunately I could not tell for sure
>>> which one was being described as superio but I think it was the
>>> cluster() alternative. I seem to remember there are discussions
>>> in the archives.
>>
>>
>> David,
>>
>> I think that you raise a good point. The example in the book (I had
>> to wait to get home to read it) is potentially different however,
>> in that the subject's eye's were randomized to treatment or
>> control, which would seem to suggest comparable baseline
>> characteristics for each pair of eyes, as well as an active
>> intervention on one side where a difference in treatment effect
>> between each eye is being analyzed.
>>
>> It is not clear from John's description above if there is one hip
>> that will be treated versus one as a control and whether the extent
>> of disease at baseline is similar in each pair of hips. Presumably
>> the timing of hip replacements will be staggered at some level,
>> even if there is comparable disease, simply due to post-op recovery
>> time and surgical risk. In cases where the disease between each hip
>> is materially different, that would be another factor to consider,
>> however I would defer to orthopaedic physicians/surgeons from a
>> subject matter expertise consideration. It is possible that the
>> bilateral hip replacement data might be more of a parallel to
>> bilateral breast cancer data, if each breast were to be tracked
>> separately.
>>
>> I have cc'd Terry here, hoping that he might jump in and offer some
>> insights into the pros/cons of using coxme versus coxph with either
>> a cluster or strata based approach, or perhaps even a frailty based
>> approach as in 9.4.1 in the book.
>>
>> Regards,
>>
>> Marc
>>
>>
>>>
>>> -- David.
>>>>
>>>> You also might find the following of interest:
>>>>
>>>> http://bjo.bmj.com/content/71/9/645.full.pdf
>>>>
>>>> http://www.ncbi.nlm.nih.gov/pubmed/22226885
>>>>
>>>> http://www.ncbi.nlm.nih.gov/pubmed/22078901
>>>>
>>>>
>>>>
>>>> Regards,
>>>>
>>>> Marc Schwartz
>>>>
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list
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>>>> posting guide http://www.R-project.org/posting-guide.html and
>>>> provide commented, minimal, self-contained, reproducible code.
>>>
>>> David Winsemius Alameda, CA, USA
>>>
>>> ______________________________________________
>>> 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.
>>
>>
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