> Patients are either fully oriented or not (1 or 2) after an hour. If
they're
> not, then the data is right censored.
It doesn't look like right censored data to me, unless the time variable
were "time to full orientation"; you labeled it "time to awake" which
appears to be something different.
Three comments:
1. If there is no right censoring (and it appears not), I would use
lmer on the awakening times, glmer on the FullyOriented variable. That
is, I agree with Burt.
Another option is GEE models
2. If you want to use a Cox model, then you can
a. Add "+ cluster(id)" to the mod
There is indeed right censoring, but I obviously didn't explain it very well.
Patients are either fully oriented or not (1 or 2) after an hour. If they're
not, then the data is right censored.
However, I don't feel that "coxme" is overkill at all, as I may also have to
account for repeated COURS
Is there any right censoring?
If not, then plain old lme, lmer, gam (in mgcv), ... etc. would seem
to me do just fine for time to waking = ORIENTATION as a response --
or are you thinking of this as interval-censored data, which it would
appear to be since you've binned the response? I strongly s
On Jul 1, 2011, at 10:22 AM, David Winsemius wrote:
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
individu
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
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(*, "dimname
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