[R-sig-ME] model specification in lmer

[Voeten, C.C.]

There are various ways to do this. The most important thing to make sure of is that the models you're comparing are both fitted either with or without REML; you can't mix ML and REML fits (that will heavily bias your LRT in favor of the ML model). You can fit the no-random-intercept model using lm(), and use anova() to compare it with a random-intercept lmer model fitted with REML=F. A (perhaps slightly better) alternative is to use gls() from nlme to fit the no-random-intercept model using REML. You can then manually calculate chi-square values like so:

> library(nlme)
> library(lme4)
Loading required package: Matrix

Attaching package: ‘lme4’

The following object is masked from ‘package:nlme’:

    lmList

> model1 <- gls(Reaction~Days,sleepstudy)
> model2 <- lmer(Reaction~Days + (1|Subject),sleepstudy)
> ( neg2ll1 <- -2*logLik(model1) )
'log Lik.' 1893.664 (df=3)
> ( neg2ll2 <- -2*logLik(model2) )
'log Lik.' 1786.465 (df=4)
> ( difference <- as.numeric(neg2ll2-neg2ll1) )
[1] -107.1986
> pchisq(difference,1)
[1] 0

Good luck!
________________________________________
Van: R-sig-mixed-models [r-sig-mixed-models-bounces at r-project.org] namens silvia.matesanzgarcia at gmail.com [silvia.matesanzgarcia at gmail.com]
Verzonden: donderdag 30 november 2017 19:55
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] model specification in lmer

Hello all

I am attempting to fit a mixed model in lmer. I have an experimental design
with families nested within populations in two different treatments, and I
want to test the effects of Pop, Trt, and Pop:Trt as fixed factors, and
Family and Family*Trt as random factors.



My full model would be:

model1=lmer(Trait~Pop*Trt + (Trt|Family)

I can then use:

model2=lmer(Trait~Pop*Trt + (1|Family)

and

anova(model1, model2) would provide signification for the interaction term.



I would need a third model with only the interaction term, so that I can
compare it to the full model and obtain significance for the family term.
But I can't figure out how to do this last part.



Can I just compare model2 to a model with no random part?



Thank you so much for your help in advance.




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