Hi Alex,
I'm slightly unclear as to why you would want to restructure your nice
six-column data.frame (why six? One column for the data and four for the
factors should make five, shouldn't it? I guess you have a subject ID in
one column?) into some monstrosity which I assume you would fill with
lots of indicator variables. R does all this for you, just do something like
library(nlme)
lme(response~factor1+factor2+factor3+factor4,random=~1|ID,data=dataset)
assuming that your data.frame is called dataset with column names
response, factor1, ..., factor4 and ID (and that the above is the model
you want). Take a look at the help page for lme() and the Orthodont data
set, which is used as an example in the lme() help page. And next time,
send along a snippet of your data.frame, that would help us help you.
HTH
Stephan
Am 07.09.2010 20:19, schrieb Walther, Alexander:
Dear list,
i am setting up a GLM for a repeated measurement ANOVA using the lm and
ANOVA function. my design contains four factors with 5, 5, 2 and 2 (=
14) levels, respectively. the data are stored in a data.frame with six
columns, one for the data themselves and the remainings for the factors
where strings indicate the factor levels in each row. now i would like
to restructure this data.frame using cbind which yields a 100 x 14
array. so far i only included two subjects in the analysis and the 100
rows emerge because each subject contributes 50 values. for the ANOVA
however, it seems to me that i should create a multi-dimensional array
where each dimension accounts for one specific factor and its levels. is
it possible to do this in R? if so, does the lm or ANOVA function
necessitates this type of array or is there yet another way to continue?
Best
Alex
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