On 10-09-20 02:09 PM, array chip wrote:
> Thank you Peter for your explanation of relationship between aov
> and lme. It makes perfect sense.
>
>
> When you said "you might have computed the average of all 8
> measurements on each animal and computed a 1-way ANOVA" for
> treatment effect, would this be the case for balanced design, or it
> is also true for unbalanced data?
>
   Only true for balanced designs

> Another question is if 1-way ANOVA is equivalent to mixed model for
> testing treatment effect, what would be reason why mixed model is
> used? Just to estimate the variance components? If the interest is
> not in the estimation of variance components, then there is no need
> to run mixed models to test treatment effects?

    If all is balanced/orthogonal/etc. and a nested design is used, *then*
there is indeed no need for mixed models in testing treatment
effects.  See e.g

Murtaugh, Paul A. 2007. Simplicity and Complexity in Ecological Data
Analysis. Ecology 88, no. 1: 56-62.
<http://www.esajournals.org/doi/abs/10.1890/0012-9658%282007%2988%5B56%3ASACIED%5D2.0.CO%3B2>

> And my last question is I am glad to find that glht() from multcomp
> package works well with a lmer() fit for multiple comparisons.
> Given Professor Bates's view that denominator degree's of freedom
> is not well defined in mixed models, are the results from glht()
> reasonable/meaningful? If not, will the suggested 1-way ANOVA used
> together with glht() give us correct post-hoc multiple comparsion
> results?
 
  I'll leave this one for someone else.

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