[R] AIC in lmer

From: Richard Chandler <rchandler_at_forwild.umass.edu>
Date: Fri 07 Oct 2005 - 21:47:24 EST


Hello all,

Is AIC calculated incorrectly in lmer? It appears as though it uses AIC = -2*logLik - 2*#parms, instead of -2*LogLik + 2*#parms? Below is output from one of many models I have tried:

Generalized linear mixed model fit using PQL

Formula: cswa ~ pcov.ess1k + (1 | year) 
   Data: ptct50.5 
 Family: poisson(log link)
      AIC    BIC    logLik deviance

 224.8466 219.19 -114.4233 228.8466
Random effects:
     Groups        Name    Variance    Std.Dev. 
       year (Intercept)   0.0062643    0.079147 
# of obs: 125, groups: year, 2

Estimated scale (compare to 1) 1.277183

Fixed effects:

              Estimate Std. Error z value Pr(>|z|) (Intercept) -0.1059628 0.1283976 -0.82527 0.4092 pcov.ess1k 0.0101182 0.0093962 1.07683 0.2816

A snip of my data:

      cswa pcov.ess250 year

[1,] 4 7.14 2004
[2,] 4 19.26 2003
[3,] 1 3.66 2004

I'm using R 2.1.1 with Windows XP.

Thanks,
Richard

-- 
Richard Chandler
Department of Natural Resources Conservation
UMass Amherst
(413)545-1237

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Received on Fri Oct 07 22:02:27 2005

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