Hi Gregory,
This is good to know! I'll try this.
Thank you very much !!
I imagine that the fact that the fact that av will be a true R object
will help the summary() function to find the good method summary.aov().
However, I tried to call explicitly summary_aov() with no success.
But I have to test it before to go further.
Thanks again !!
-Etienne
Gregory Warnes a écrit :
>
> Hi Etienne,
>
> The basic problem is that under the default conversion mode
> (BASIC_CONVERSION) all R objects are converted to roughly-equivalent
> python structures. As a consequence, the object 'av' isn't actually
> an R object, so r.summary(av) won't treat it as such. The simplest
> solution is to change the conversion mode to NO_CONVERSION adn then
> explicitly request conversion of an object when you need the python
> version. IE:
>
>> set_default_mode(NO_CONVERSION)
>> v = r.aov(r.formula("score~factor+Error(id_subject/factor)"),
>> data=Res)set_default_mode(BASIC_CONVERSION)
>> set_default_mode(BASIC_CONVERSION)
>> r.summary(av)
>
> -G
>
> On Dec 18, 2007, at 1:52PM , Etienne Gaudrain wrote:
>
>> 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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