[R] R^2 from lme function

Martin Henry H. Stevens HStevens at MUOhio.edu
Mon May 14 18:55:25 CEST 2007


Hi Cleber,
By "full" I simply meant "not REML." the function assumes that the  
fixed effects were estimated using REML criteria, and using update()  
simply changes that to ML. If the model was fit originally with ML,  
it shouldn't make any difference.

I am reasonably sure that it should not matter whether there is an  
intercept. ML estimates are invariant to fixed effects structure,  
whereas REML depends upon it.

Cheers,
Hank

On May 14, 2007, at 11:55 AM, Cleber Borges wrote:

> Hi Martin,
>
> many thanks for your tip!
>
> but,                                        { :-(   }
> what it 'full MLE' ?   how to calculate? it is a saturated model???
>
> and
>
> it is valid for 'no-intercept model?
>
>
> Many thanks again...
>
> Cleber
>
>
>> Hi Cleber,
>> I have been using this function I wrote for lmer output. It should be
>> easy to convert to lme. As with everything, buyer beware. Note  
>> that it
>> requires (full) maximum likelihood estimates.
>>
>>
>> Rsq <- function(reml.mod) {
>>  ## Based on
>>   ## N. J. D. Nagelkerke. A note on a general definition
>>   ## of the coefficient of determination. Biometrika, 78:691–692,  
>> 1991.
>>   ml.mod <- update(reml.mod, method="ML")
>>   l.B <- logLik(ml.mod)
>>   l.0 <- logLik( lm(ml.mod at y ~ 1) )
>>   Rsq <- 1 - exp( - ( 2/length(ml.mod at y) ) * (l.B - l.0) )
>> Rsq[1]
>> }
>>
>> Hank
>>
>>
>>
>>
>>> Hello allR
>>> How to access R^2 from lme object?
>>> or how to calculate it?
>>> ( one detail: my model do not have a intercept )
>>> thanks in advanced
>>> Cleber
>
> 		
> _______________________________________________________
>
> Experimente já e veja as novidades.
>
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Dr. Hank Stevens, Assistant Professor
338 Pearson Hall
Botany Department
Miami University
Oxford, OH 45056

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http://www.cas.muohio.edu/~stevenmh/
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