Dear R-list!
My question is related to an Anova including within and between subject
factors and unequal group sizes.
Here is a minimal example of what I did:
library(car)
within1 <- c(1,2,3,4,5,6,4,5,3,2); within2 <- c(3,4,3,4,3,4,3,4,5,4)
values <- data.frame(w1 = within1, w2 = within2)
values <- as.matrix(values)
between <- factor(c(rep(1,4), rep(2,6)))
betweenanova <- lm(values ~ between)
with <- expand.grid(within = factor(1:2))
withinanova <- Anova(betweenanova, idata=with, idesign=
~as.factor(within), type = "III" )
I do not know if this is the appropriate method to deal with unbalanced
designs.
I observed, that SPSS calculates everything identically except the main
effect of the within factor, here, the SSQ and F-value are very different
If selecting the option "show means", the means for the levels of the
within factor in SPSS are the same as:
mean(c(mean(values$w1[1:4]),mean(values$w1[5:10]))) and
mean(c(mean(values$w2[1:4]),mean(values$w2[5:10]))).
In other words, they are calculated as if both groups would have the
same size.
I wonder if this is a good solution and if so, how could I do the same
thing in R?
However, I think if this is treated in SPSS as if the group sizes are
identical,
then why not the interaction, which yields to the same result as using
Anova()?
Many thanks in advance for your time and help!
______________________________________________
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.
