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

[Bradley Carlson]

I feared that might be the situation - thanks for confirming. I'll be
toying with some creative options then. Thanks again,

Brad

On Mon, Aug 17, 2015 at 7:26 PM, Ken Beath <ken.beath at mq.edu.au> wrote:

> 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
>>
>>         [[alternative HTML version deleted]]
>>
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>
>
>
> --
>
> *Ken Beath*
> Lecturer
> Statistics Department
> MACQUARIE UNIVERSITY NSW 2109, Australia
>
> Phone: +61 (0)2 9850 8516
>
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