[R-sig-ME] Coefficient of determination (R^2) when using lme()

[Jarrett Byrnes]

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.

r2.corr.lmer<-function(lmer.object){
         summary(lm(attr(lmer.object, "y") ~ fitted (lmer.object))) 
$r.squared}


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.
> Cheers,
> Hank
> 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
>>
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