[R] Multilevel Survival Analysis - Cox PH Model

[David Winsemius]

On Jul 1, 2011, at 10:10 AM, dunner wrote:

> Hello all, thanks for your time and patience.
>
> I'm looking for a method in R to analyse the following data:
>
> Time to waking after anaesthetic for medical procedures repeated on  
> the same
> individual.
>
>> str(mysurv)
> labelled [1:740, 1:2] 20  20  15  20  30+ 40+ 50  30  15  10  ...
> - attr(*, "dimnames")=List of 2
>  ..$ : NULL
>  ..$ : chr [1:2] "time" "status"
> - attr(*, "type")= chr "right"
> - attr(*, "units")= chr "Day"
> - attr(*, "time.label")= chr "ORIENTATION"
> - attr(*, "event.label")= chr "FullyOrientated"
>
> mysurv is constructed from the following data:
>
> head(data.frame(MRN, ORIENTATION, FullyOrientated))
>
>       MRN ORIENTATION FullyOrientated
> 1 0008291           20               2
> 2 0008469           20               2
> 3 0008469           15               2
> 4 0010188           20               2
> 5 0013664           30               1
> 6 0014217           40               1
>
>
> I had planned to use a Cox PH model to analyse time to waking  
> (ORIENTATION =
> 10, 15, 20 mins ....... 50 mins) and whether or not people (MRN) are  
> fully
> awake within an hour (FullyOrientated). I've put  GENDER, etc. into  
> the
> model but I have the following bias:
>
> The procedure is repeated weekly on each individual (MRN), so each
> individual has 5-9 cases associated with them. Currently I am  
> including
> these in the model as if they were independent.
>
> Is there a way to account for the non-independence of these waking  
> times?
>
> I'm thinking of something similar to the NLMER package and  
> Multilevel /
> Mixed Effects analysis as described in Pinheiro and Bates.

Have you looked at the coxme package?

-- 

David Winsemius, MD
West Hartford, CT