[R-sig-ME] Residual variance for mixed effects survival analysis

[Ken Beath]

For Cox survival analysis there is no residual as part of the model, hence
no residual variance.

Ken

On 18 August 2015 at 02:01, Bradley Carlson <carbrae at gmail.com> wrote:

> I'm working on an analysis of the amount of time it takes an animal to
> perform a behavior. This data is right-censored, as we stopped waiting
> after 10 minutes and simply had to record "10+ minutes" for any animals
> that didn't perform the behavior. The data is well suited for a Cox
> proportional hazards 'survival' analysis in this regard. However, I have
> multiple measurements of each individual animal (random effect) and would
> like to quantify the individual repeatability of the behavior in addition
> to the effect of covariates. In a typical LMM, this would be the (variance
> among random intercepts) / (variance among random intercepts + residual
> variance).
>
> I can fit a mixed effects survival analysis in the package 'coxme'. It
> provides a random effect variance, but no residual variance. Is it
> possible, given the mechanics of fitting an ME survival analysis, to get a
> residual variance?
>
> Thank you in advance!
>
> --
>
> Bradley Evan Carlson
> Assistant Professor of Biology
> Wabash College, Crawfordsville IN
>
> Email: *carlsonb at wabash.edu* <+carlsonb at wabash.edu>
> Website: https://sites.google.com/site/bradleyecarlson/home
>
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>
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-- 

*Ken Beath*
Lecturer
Statistics Department
MACQUARIE UNIVERSITY NSW 2109, Australia

Phone: +61 (0)2 9850 8516

Level 2, AHH
http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken/

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