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.
I'd be appreciative of any help at all?
Thanks again,
R
--
View this message in context:
http://r.789695.n4.nabble.com/Multilevel-Survival-Analysis-Cox-PH-Model-tp3638278p3638278.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@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.
