[R-sig-ME] interpretation of split-plot design with results from lmer

[Austin Frank]

On Mon, Mar 12 2007, Irene Mendoza Sagrera wrote:

> After having reading as many documents as I could about the lmer
> function and the lack of p-values, I need to recognize that I
> haven’t understood the right way of extracting conclusions when
> using the lmer function. Maybe I would need more statistical
> knowledge or read any other book (please, any suggestion?), but if
> you give me any help, I would be very grateful.

> I’m trying to analyze a field experiment with a split-plot design.
> ...
>
> Sincerely, for me now is the great deal. Without any p-value, how
> can I know if a fixed factor is significant for the response
> variable? What is the interpretation of these results? How I should
> present the information in a correct way to editors and referees
> (and for me, to understanding the effects)?

Irene--

While the examples won't be directly related to your field, I have
found that a paper by Baayen, Davidson, and Bates has a very clear
presentation of the analysis of a split-plot design with lme4.  In
addition, the article has a corresponding R package called languageR
that provides some functionality that would be useful in answering
your main question.  Taken together, I think the paper and the R
package are a very useful addition to the available materials on mixed
effects models.  I'm grateful to the authors for putting both
together!

You can find the submitted pdf on Baayen's publications page, at
http://www.mpi.nl/world/persons/private/baayen/publications/baayenDavidsonBates.pdf.

Good luck with your analysis!
/au

-- 
Austin Frank
http://aufrank.net
GPG Public Key (D7398C2F): http://aufrank.net/personal.asc