Thanks for all of your help, David, I finally got it. Here's some generic
syntax in case it helps someone else down the road (using a 4-way ANOVA
with repeated measures on all factors):
# LOAD DATA
data <- read.table("PATH\\datafile.txt")
# RUN THE ANOVA
data.aov <- aov(y ~ factor(x1)*factor(
On Dec 13, 2008, at 2:15 PM, js.augus...@gmail.com wrote:
> Does not this give you what you need?
> model.tables(rawfixtimedata.aov,"means", se=TRUE)
I tried that, but get an error:
SEs for type 'means' are not yet implemented
I don't get that error. Using the example and this call
model.ta
> Does not this give you what you need?
> model.tables(rawfixtimedata.aov,"means", se=TRUE)
I tried that, but get an error:
SEs for type 'means' are not yet implemented
Maybe I'm not using the correct terminology to describe what I need to do.
Using the main effect of Marking as an example, I h
On Dec 13, 2008, at 11:37 AM, Jason Augustyn wrote:
Hi David, thanks for the quick response. I did look at the help
files for model.tables and se.contrast and neither seemed
appropriate. I probably wasn't clear enough in my original email, so
here's more information:
I'm analyzing data f
Hi David, thanks for the quick response. I did look at the help files for
model.tables and se.contrast and neither seemed appropriate. I probably
wasn't clear enough in my original email, so here's more information:
I'm analyzing data from a psychology experiment on how people allocate
visual atten
On Dec 12, 2008, at 10:59 PM, js.augus...@gmail.com wrote:
Hi all,
I'm quite new to R and have a very basic question regarding how one
gets
the standard error of the mean for factor levels under aov. I was
able to
get the factor level means using:
summary(print(model.tables(rawfixtimedat
Hi all,
I'm quite new to R and have a very basic question regarding how one gets
the standard error of the mean for factor levels under aov. I was able to
get the factor level means using:
summary(print(model.tables(rawfixtimedata.aov,"means"),digits=3)),
where rawfixtimedata.aov is my aov m
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