[R] Two-way Anova

[Mike Lawrence]

Using traditional ANOVA, you'd have to drop either cases or time
points with missing data. Using linear mixed effects analysis, you'd
be able to use all the data. LME also has the benefit of *not*
assuming sphericity, which is good for data like yours (many measures
across few cases) where the traditional ANOVA sphericity assumption is
unlikely to hold.

Your dependent variable, % valid, suggests that there's some more raw
representation of the data that may be better to look at. For example,
if % valid is derived from, say, the success/failure rate of 10
observations per sample/timepoint, you might want to take a look the
lme4 package (as suggested in a previous post:
https://stat.ethz.ch/pipermail/r-sig-mixed-models/2008q3/001160.html )

On Tue, May 12, 2009 at 6:03 AM, Alan O'Loughlin <OLougA at wyeth.com> wrote:
> Hello,
>
> I'm trying to do a comparsion on a large scale say 10L bottle of liquid and a small scale bottle of liquid 0.5L, I have 5 different samples from each and they are measured over the space of 8 days as % viability and the % viability decreases over time. However not all 10 samples got measured every day. How would I do a two-way anova on this in R?
>
> Thanks for any help.
>
> Regards,
> Al
>
>        [[alternative HTML version deleted]]
>
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-- 
Mike Lawrence
Graduate Student
Department of Psychology
Dalhousie University

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