hierarchical linear models, mixed models and lme

Dieter Menne · 2007-12-20T17:54:09Z

Nicolas Ris sophia.inra.fr> writes: > I am trying to analyse the data of the box 10.5 in the Biometry from > Sokal and Rohlf (2001) using R. This is a three-level nested anova with > equal sample size : 3 different treatments are compared ; 2 rats (coded > 1 or 2) / treatment are studied ; 3 preparations (coded 1, 2 or 3) / > rats are available ; 2 readings of the glycogen content / preparations > are realised. Treatment is fixed whereas Rats (nested in Treatment) and

Dieter Menne

Thu, Dec 20, 2007 9:54 AM

Nicolas Ris <Nicolas.Ris <at> sophia.inra.fr> writes:

Since your factors are codes as numbers, the first thing I would check if these
are really factors in your data frame. If these are numeric, you will get a
regression and degrees of freedom are totally off. Try

box105.gd$rats = as.factor(box105.gd$rats)
box105.gd$prep = as.factor(box105.gd$prep)

I am sure there will be some differences to Sokal/Rohlf afterwards, but you
should come closer. Please post a complete, self-running examples if you have
more questions.

Dieter

hierarchical linear models, mixed models and lme

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