anova(lm(OQtil4 ~ Tone, data=gesamt))
and similarly for your other response variables. There are ways of putting this kind of thing in a loop, storing only the p values or whatever you want. However, unless you need a routine to do this many times, it's probably best to just do it like this and be done with it.
hope this helps. spencer graves
Winfried Theis wrote:
Hi Britta!
On Tue, 2003-09-09 at 10:57, Britta Lintfert wrote: [snip]
now I want to know, if there are significant differents in the variables OQ, GO, SK, RC depending on Tone. This I can do with an ANOVA , or??
Yes, this is correct.
But when I start aov in R I get the following message:
anova1 <- aov(Tone ~ OQtil4*OQ0*GOtil4*GO0*SKrhsJ*SK0*RCrhsJ*RC0, data=gesamt) Warning message: "-" not meaningful for factors in: Ops.factor(y, z$residuals)
What's wrong with my Data?
Nothing. It is your call to aov that is wrong. Formulas in R are formulated as "Dependent variable" ~ "influences". So what you are trying to do is to explain Tone by all your other variables and their interactions. If your variables are independent you may simply go ahead and use aov on each of them. Look first for a book on multivariate linear models...
Thanks for helping me
You're welcome.
Winfried
Britta
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