[R-sig-ME] [R] lmm WITHOUT random factor (lme4)

[David Duffy]

On Fri, 18 Mar 2011, ONKELINX, Thierry wrote:

> What worries me is that the loglikelihood of a lm() model and the 
> equivalent gls() model is different. Although both models should be 
> mathematically identical. Assuming that the loglikelihood is calculated 
> on the same way within a package, I therefore have more confidence in 
> comparing two models from the same package, thus gls() versus lme(). 
> Furthermore, I get an error when doing an anova between a lm() and a 
> lme() model.


> logLik(fm)
'log Lik.' -950.1465 (df=3)
> logLik(fm, REML=T)
'log Lik.' -946.8318 (df=3)


> anova(fm1, fm0, fm)
     Model df      AIC      BIC    logLik   Test  L.Ratio p-value
fm1     1  4 1794.465 1807.192 -893.2325
fm0     2  3 1899.664 1909.209 -946.8318 1 vs 2 107.1986  <.0001
fm      3  3 1899.664 1909.209 -946.8318


-- 
| David Duffy (MBBS PhD)                                         ,-_|\
| email: davidD at qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
| Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
| 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v