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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