Re: [R] effect sizes in lme/ multi-level models

From: Spencer Graves <spencer.graves_at_pdf.com>
Date: Tue 14 Feb 2006 - 03:46:38 EST

          The "eta^2" you describe looks something like an R^2 (or maybe a partial R^2), and CohensD looks like a Student's t, at least to me. The problem with generalizing these to multi-level models is deciding which components of variance to include where. If you can answer that, I think you can find all the pieces you need by trying 'methods(class="lme")'. I just got 32 items on that list, but you might get a different number unless you have exactly the same packages (and versions) attached as I did just now. From this list of 32, I suggest you look first at "fixef", "ranef", and "VarCorr".

	  hope this helps.
	  spencer graves

Leo Gürtler wrote:

> Dear alltogether,
>
> I am searching for a way to determine "effect size" in multi-level
> models by using lme().
> Coming from Psychology, for ordinary OLS there are measures (for
> meta-analysis, etc.) like
>
> CohensD <- (mean_EG - mean_CG) / SD_pooled
>
> or
>
> (p)eta^2 <- SS_effect / (SS_effect + SS_error)
>
> I do not intend to lead a discussion of the usefulness of such measures
> as long as the standards of psychological journals (e.g. as defined by
> the APA) order them.
> However, I wondered how to determine measures of effect size in lme.
> Pinheiro&Bates (2000) do not touch that topic.
> I assume that as long as a grouping structure is present, the formular
> of CohensD (see above) has to be corrected to give respect to the
> grouping structure. Is there any equivalent measure like eta^2,
> partial-eta^2, etc.?
>
> Can anybody help me with formulas, R code or some references?
>
> Thank you very much,
>
> thanks in advance,
>
> leo gürtler
>



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