Thanks for your insight.

Actually I will ultimately have 25 sites in each set. I'm just trying to
get the model set up and understood in R. And, yes, I understand with 5
sites in each category there would be power issues. But my question is not
about basic frequentist distribution theory or power. Rather, how does one
go about setting different random effect error variances by group using
lme?

In any case, I'll just use a Bayesian model in JAGS, something I'm way more
comfortable with in parameterizing and something that has more flexibility
anyway to make the inferences I'd like.

However, despite that, if anyone knows how to incorporate or assess
different random effects by group using lme, your input would be welcome.

And, I'm 99% sure the varIdent function by group just gives a different,
constant error variance by the grouping variable.

Kris


On Wed, Jul 31, 2013 at 4:35 AM, ONKELINX, Thierry <Thierry.ONKELINX@inbo.be
> wrote:

> Kristofor,
>
> Don't forget that you have only 10 sites. That gives you an estimate of
> the random intercept variance but a rather poor estimate. The ratio of the
> sample variance and the true variance follows a Chisq distribution. With
> only 10 sites you get very wide confidence intervals on the variance. With
> 5 sites the get even wider, thus making a comparison between then
> irrelevant. You need a lot of data to get decent variance estimates.
>
> CI.ratio = chisq(c(0.025, 0.975), df = n - 1) / (n - 1)
>
> n = 5: c(0.12, 2.8)
> n = 10: c(0.3, 2.1)
> n = 30: c(0.55, 1.58)
> n = 100: c(0.74, 1.30)
> n = 200: c(0.81, 1.21)
>
> So I would not even try to model a different random effect variance per
> treatment with your dataset.
>
> Best regards,
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
> + 32 2 525 02 51
> + 32 54 43 61 85
> Thierry.Onkelinx@inbo.be
> www.inbo.be
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of.
> ~ Sir Ronald Aylmer Fisher
>
> The plural of anecdote is not data.
> ~ Roger Brinner
>
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
> -----Oorspronkelijk bericht-----
> Van: r-sig-mixed-models-bounces@r-project.org [mailto:
> r-sig-mixed-models-bounces@r-project.org] Namens David Duffy
> Verzonden: woensdag 31 juli 2013 8:15
> Aan: Kristofor Voss
> CC: r-sig-mixed-models@r-project.org
> Onderwerp: Re: [R-sig-ME] Nested random effect within fixed effect factor?
>
> On Wed, 31 Jul 2013, Kristofor Voss wrote:
>
> > Thanks. Yes this partitions the error variance, but not the random
> > effect variance. That part is working fine (and in fact matches what I
> > get from running both subsets). But still curious about the random
> > effects being different.
>
> I'm not sure you're right in characterizing it that way.  My simple-minded
> understanding (I would be grateful for correction) is that you can get
> equivalent models by either modeling the off-diagonal covariances for Z or
> for e, since here you don't have an informative design (some clusters or
> individuals receiving both treatments).
>
>
> | David Duffy (MBBS PhD)                                         ,-_|\
> | email: davidD@qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
> | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
> | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> * * * * * * * * * * * * * D I S C L A I M E R * * * * * * * * * * * * *
> Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver
> weer en binden het INBO onder geen enkel beding, zolang dit bericht niet
> bevestigd is door een geldig ondertekend document.
> The views expressed in this message and any annex are purely those of the
> writer and may not be regarded as stating an official position of INBO, as
> long as the message is not confirmed by a duly signed document.
>



-- 
Kristofor A. Voss
Ph.D. Candidate
Bernhardt Lab
Nicholas School of the Environment
Duke University
P.O. Box 90328
Durham, NC 27708
619-249-3614
kristofor.voss@duke.edu
Office: FFSC 3304

	[[alternative HTML version deleted]]

