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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https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide

http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.