[R-sig-ME] bootstraping a mixed-model (lme)

[Ken Beath]

The sampling of complete clusters works better, at least for normal data.
See Davison and Hinkley "Bootstrap Methods and their Application" section
3.8. If the clusters are large then there will be no difference if sampling
within clusters is performed as well, but there doesn't seem to be any
point.

On 8 April 2015 at 13:25, Roslyn Dakin <roslyn.dakin at gmail.com> wrote:

> This question is in response to Ken's point about bootstrapping mixed
> models (that you have to resample whole clusters/subjects for the
> nonparametric bootstrap). Why can't you nonparametric bootstrap a mixed
> model by stratified bootstrapping? i.e., resampling within each level of
> the random effect, assuming you have a decent number of observations for
> each level
>
> Many thanks,
> Roz
>
> --
>
> Roslyn Dakin, PhD
> Department of Zoology
> University of British Columbia
>
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>
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-- 

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

Phone: +61 (0)2 9850 8516

Building E4A, room 526
http://stat.mq.edu.au/our_staff/staff_-_alphabetical/staff/beath,_ken/

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