Why don't you put your R code in file.R:
library('stats')
my.summary = function(Res) {
av <- aov( score~factor+Error(id_subject/factor), data=Res)
summary(av)
}
then from python:
r.source("file.R")
r.my_summary(Res)
???
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Etienne Gaudrain
Sent: Tuesday, December 18, 2007 10:53 AM
To: [email protected]
Subject: [Rpy] Repeated measure ANOVA : formula and summary problem
Hi everyone,
I'm new to RPy, and I came to this terrific module as I was used to make some
of my analyses in R, and I came to Python in replacement of Matlab. Formerly, I
manipulated data with Matlab, put it in a MySQL database, and made my stats in
R via ODBC. I'm now thinking about jumping one step by calling R directly from
Python with RPy.
The analysis I almost always have to do is a repeated measure ANOVA. The way I
do this in R is :
# after odbc connection and sql query, Res contains my data
library('stats')
av <- aov( score~factor+Error(id_subject/factor), data=Res)
summary(av)
Now I tried the same in RPy :
# retrieve data from sql query, Res is a dictionnary
r.library('stats')
av = r.aov("score~factor+Error(id_subject/factor)", data=Res)
This fails saying that "Error" isn't defined in the dataframe...
After reading some R doc about GLM, I found that using the R function formula()
seemed to solve this problem:
av = r.aov(r.formula("score~factor+Error(id_subject/factor)"), data=Res)
r.summary(av)
However, a new problem rose in r.summary(). This function returns something
that isn't readable, and that does not contain the p values, or anything
similar. It seems that the r.summary_aov() function might be adequat, but this
function returns an Error saying that there is a NaN somewhere...
Does anybody have an advice on how to perform the repeated measure ANOVA?
Thanks!
-Etienne
PS : I use Windows XP, Python 2.5.1, Numpy 1.0.3.1 and RPy 1.0.1-Numpy-py2.5
and R 2.6.1.
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