Hello,

I have a simple question about using the aov function syntax (ie. * + or :)
for the interaction of 2 factors. I have read the help files, and researched
other sites, and have included my source files. My goal is to measure the
signifigance of the interaction between population and condition (aka.
population:condition). I can't seem to figure it out.

1. In the first example the significance of population:condition works with
the "allData" but not with the "studentData." Can you please explain why it
fails and how I can fix it?

2. In the second example I can get the measure the significance of
population:condition with 2 different methods, but I get 2 different results
(using the "allData" source). Can you please explain why these Pr(>F) values
are different?

Thank you so much for your help!!

Sincerely,

Dave Deriso
UCSD Psychiatry


#Example 1 ---------------------------COPY & PASTE THE FOLLOWING

#import the data
allDataSource="http://files.davidderiso.com/r/allData.data";
allData.import=read.table(allDataSource,header=T)
studentDataSource="http://files.davidderiso.com/r/allData.data";
studentData.import=read.table(studentDataSource,header=T)


#aov for allData WORKS
allData.integral.aov = aov(integral~population*condition,
data=allData.import)
summary(allData.integral.aov)

#aov for studentData DOES NOT GIVE Pr(>F) of population:condition
studentData.integral.aov = aov(integral~population*condition,
data=studentData.import)
summary(studentData.integral.aov)



#Example 2 ---------------------------COPY & PASTE THE FOLLOWING

#population:condition has a Pr(>F) of 0.96372
allData.integral.aov = aov(integral~population*condition,
data=allData.import)
summary(allData.integral.aov)

#population:condition has a Pr(>F) of 1.070e-06 ***
allData.integral.aov = aov(integral~population:condition,
data=allData.import)
summary(allData.integral.aov)

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