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

Ken Beath ken.beath at mq.edu.au
Tue Aug 18 01:26:11 CEST 2015

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


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
>         [[alternative HTML version deleted]]
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models


*Ken Beath*
Statistics Department

Phone: +61 (0)2 9850 8516

Level 2, AHH

CRICOS Provider No 00002J
This message is intended for the addressee named and may...{{dropped:9}}

More information about the R-sig-mixed-models mailing list