Dear list,

Please excuse my ignorance, but I'm trying to model some data using the lme
package. vot is a numeric response, and condition, location and obs are all
categories.
This works:

> anova(vot.lme <- lme(vot ~ condition * location *
obs,data=mergedCodesL,random= ~1 |patient))
                       numDF denDF  F-value p-value
(Intercept)                1  1898 462.7519  <.0001
condition                  2  1898   8.4126  0.0002
location                   1    12   0.0272  0.8718
obs                        2  1898 472.5526  <.0001
condition:location         2  1898   1.0467  0.3513
condition:obs              4  1898   1.0683  0.3706
location:obs               2  1898   9.7067  0.0001
condition:location:obs     4  1898   4.6143  0.0010


If I then would like to do post-hoc testing, I found in the email archives
that I could use the glht function of multcomp - something like

summary(glht(vot.lme, linfct=mcp(obs = "Tukey")))

However, if I would like to investigate the condition:location:obs -
interaction. What do I do then?


Best!

/Fredrik
-- 
"Life is like a trumpet - if you don't put anything into it, you don't get
anything out of it."

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