[R-sig-ME] Coefficient of determination (R^2) when using lme()
jebyrnes at ucdavis.edu
Tue Apr 1 16:40:16 CEST 2008
This came up with a reviewer when I was using glms as well. I've
become fond of using the R^2 of the correlation between the fitted and
observed values. It's easily interpretable by a general audience.
summary(lm(attr(lmer.object, "y") ~ fitted (lmer.object)))
On Apr 1, 2008, at 3:37 AM, MHH Stevens wrote:
> Hi R.S.,
> This quantity is not clearly defined for mixed models --- should it
> include that which is "explained" by the random effects? What would
> it mean to "explain" a response with a variance? In any event, try
> searching R-help lists for Coefficient of determination AND lme.
> On Apr 1, 2008, at 6:17 AM, R.S. Cotter wrote:
>> Dear mixed models users,
>> I have recently started using R, and I have learned to use lme ().
>> Is it possible to interpret coefficient of determination (R^2) when
>> using lme ()?
>> Best Regards
>> R.S. Cotter
>> R-sig-mixed-models at r-project.org mailing list
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