[R-sig-ME] logLik df in lme vs. lmer

[Martin Maechler]

>>>>> "AB" == Andrew Beckerman <a.beckerman at sheffield.ac.uk>
>>>>>     on Thu, 3 Apr 2008 15:43:55 +0100 writes:

    AB> Dear all -
    AB> R 2.6.2, lme4 version 0.99875-9, OSX.

If you use any recent R-forge version of 'lme4'
you will see that the degrees of freedoms 
are 6 and 5  (instead of 5 and 4) for your two examples.

You can get the R-forge version by

install.packages("lme4",repos="http://R-Forge.R-project.org")
library(lme4)

If you want to have it in a different than default library
(because you would want the "old" CRAN-lme4 by default),
you'd need something like

myLib <- "......./my_library"
##        ^^^^^^^^^^^^^^^^^^  a place where you have WRITE permission
dir.create(myLib)
install.packages("lme4",repos="http://R-Forge.R-project.org",
		 lib = myLib)
library(lme4, lib = myLib)


Martin




    AB> We have noticed that lme and lmer produce different estimates of the  
    AB> number of paramters in the estimation of the logLik.  While these are   
    AB> different, the logLik is not (good), but ensuing calculations of AIC  
    AB> can be.

    AB> According to some textbooks (i.e. Burnham and Anderson), the number of  
    AB> paramters is calcuated as the intercept + betas+ random effects levels  
    AB> (?) + a term for the residual variance.  In the example below  
    AB> (sleepstudy from lmer), that calculation results in df=5, as indicated  
    AB> in lmer but not in lme.

    AB> library(lme4)

    AB> wrk<-sleepstudy # data from lmer package

    AB> fm.lmer <- lmer(Reaction ~ Days + (Days|Subject), wrk,method="ML")
    AB> logLik(fm.lmer) # df = 5
    AB> fm.lmer
    AB> AIC(logLik(fm.lmer))

    AB> detach(package:lme4)

    AB> library(nlme)

    AB> fm.lme <- lme(Reaction ~ Days,random=~Days|Subject, wrk,method="ML")
    AB> summary(fm.lme)
    AB> logLik(fm.lme) # df=6
    AB> AIC(logLik(fm.lme))

    AB> However, we have also seen lmer appear to "underestimate" and lme get  
    AB> it right -

    AB> # continuing from above

    AB> wrk2<-Orthodont # data from nlme package
    AB> fm.lme2 <- lme(distance ~ age + Sex, data = wrk2, random = ~  
    AB> 1,method="ML")
    AB> fm.lme2
    AB> logLik(fm.lme2) # df=5 (correct?)

    AB> detach(package:nlme)

    AB> library(lme4)

    AB> fm.lmer2 <- lmer(distance ~ age + Sex+(1|Subject), data = wrk2,  
    AB> method="ML")
    AB> fm.lmer2
    AB> logLik(fm.lmer2) # df=4 (now underestimated?)

    AB> Does anyone know what is going on?  Obviously, we can just specify the  
    AB> df in AIC calculations by hand, but AIC() uses the df from logLik (),  
    AB> which seems to vary.

    AB> I've noticed this question here as well.

    AB> http://tolstoy.newcastle.edu.au/R/e4/help/08/02/3988.html

    AB> Cheers
    AB> andrew


    AB> ---------------------------------------------------------------------------------
    AB> Dr. Andrew Beckerman
    AB> Department of Animal and Plant Sciences, University of Sheffield,
    AB> Alfred Denny Building, Western Bank, Sheffield S10 2TN, UK
    AB> ph +44 (0)114 222 0026; fx +44 (0)114 222 0002
    AB> http://www.beckslab.staff.shef.ac.uk/

    AB> _______________________________________________
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