On 1/3/2012 9:36 PM, maximilian.mueller wrote:
Here is the syntax:
options(contrasts=c("contr.sum", "contr.poly"))
read.csv2("test21.csv") -> dat3
mod3 <- lm(cbind(umsatz_t1, umsatz_t2, umsatz_t3, umsatz_t4) +
cbind(ebitda_t1, ebitda_t2, ebitda_t3, ebitda_t4)
+ ~ 1, data=dat3)
idata3 <- data.frame(Umsatz=factor(1:4), EBITDA=factor(1:4))
aov3 <- Anova(mod3, idata=idata3, idesign= ~Umsatz+EBITDA, type="III")
Fehler in check.imatrix(X.design) :
Terms in the intra-subject model matrix are not orthogonal.
summary(aov3, multivariate=F)
That's because you've defined two identical factor variables.
idata3<- data.frame(Umsatz=factor(1:4), EBITDA=factor(1:4))
> idata3 <- data.frame(Umsatz=factor(1:4), EBITDA=factor(1:4))
> idata3
Umsatz EBITDA
1 1 1
2 2 2
3 3 3
4 4 4
>
If your data is a doubly-multivariate design with two repeated variables
Umsatz and EBIDTA crossed with 4 time points each, you might want to look
at the vignette "HE Plots for Repeated Measures Designs" in the heplots
package for theory and examples
vignette("repeated", package="heplots")
--
Michael Friendly Email: friendly AT yorku DOT ca
Professor, Psychology Dept.
York University Voice: 416 736-5115 x66249 Fax: 416 736-5814
4700 Keele Street Web: http://www.datavis.ca
Toronto, ONT M3J 1P3 CANADA
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