Displaying 3 results from an estimated 3 matches for "lme4_1".
Did you mean:
lme4
2004 Aug 12
0
Re: R-help Digest, Vol 18, Issue 12
...ollowed the suggestion to fit the exact same model with
> lme4. However, format of the anova output does not give me the
> estimation in the way nlme does. More importantly, the degrees of
> freedom in the denominator dont change, theyre still large:
> > library(lme4)
> > lme4_1<-lme(RT~fact1*fact2*fact3,random=~1|sub,data=myData)
> > anova(lme4_1)
> Analysis of Variance Table
>
> Df Sum Sq Mean Sq Denom F value Pr(>F)
> fact1I 1 2.709e-07 2.709e-07 48 21.9205 2.360e-05
> ***
> fact2I...
2004 Aug 11
1
Fwd: Enduring LME confusion… or Psychologists and Mixed-Effects
In my undertstanding of the problem, the model
lme1 <- lme(resp~fact1*fact2, random=~1|subj)
should be ok, providing that variances are homogenous both between &
within subjects. The function will sort out which factors &
interactions are to be compared within subjects, & which between
subjects. The problem with df's arises (for lme() in nlme, but not in
lme4), when
2004 Aug 10
4
Enduring LME confusion… or Psychologists and Mixed-Effects
Dear ExpeRts,
Suppose I have a typical psychological experiment that is a
within-subjects design with multiple crossed variables and a continuous
response variable. Subjects are considered a random effect. So I could model
> aov1 <- aov(resp~fact1*fact2+Error(subj/(fact1*fact2))
However, this only holds for orthogonal designs with equal numbers of
observation and no missing values.