Hello fellow R users,
I am having a problem finding the estimates for some overall treatment
effects for my mixed models using 'lme' (package nlme). I hope someone
can help.
Firstly then, the model:
The data: Plant biomass (log transformed)
Fixed Factors: Treatment(x3 Dry, Wet, Control) Year(x8 2002-2009)
Random Factors: 5 plots per treatment, 5 quadrats per plot (N=594 (3*5*5*8)
with 6 missing values).
I am modelling this in two ways, firstly with year as a continuous variable
(interested in the difference in estimated slope over time in each treatment
'year*treatment'), and secondly with year as a categorical variable
(interested in difference between 'treatments').
When using Year as a continuous variable, the output of the lme means
that I can compare the 3 treatments within my model...
i.e. it takes one of the Treatment*year interactions as the baseline
and compares (contrasts) the other two to that.
I can then calculate the overall treatment*year effect using
'anova.lme(Model).
However, the problem comes when I use Year as a categorical variable.
Here, I am interested solely in the Treatment effect (not the
interaction with year). However, the output for the two labelled
'Treatment's against the third comparison, are not the overall effect
but are a comparison within a year (2002). I can still get my overall
effect (using anova.lme) but how do I calculate the estimates (with
P-Values if possible) for each seperate overall treatment comparison
(not within year). I tried 'glht' (package 'multicomp') but this only
works if there are no interactions present, otherwise again it gives a
comparison for one particular year.
Very grateful for any assistance,
Mark
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
