David and Peter,
Thanks so much for all of your help, I think I understand R much better
as a result. Omitting the Error() term in my aov does indeed allow me to
get SE means, so I guess that was the issue. I suppose I can go back and
calculate the SE values for each p*t entry (averaged across subject)
from Matlab.
By the way, the reason I separated the p and t objects derived from
rate_data in my initial example was for readability. If I do it as below
then I get the same result.
In any case, again many thanks for your help. Cheers and Happy Holidays.
Jon
rate_data=read.table("/Users/jonprince/Desktop/attend_pitch_3p3t.txt")
rate_data$p=factor(rate_data$V3)
rate_data$t=factor(rate_data$V2)
rate_data$subj=factor(rate_data$V1)
rate_data$rate=rate_data$V4
fm=aov(rate_data$rate ~ rate_data$p*rate_data$t +
Error(rate_data$subj/(rate_data$p*rate_data$t)),rate_data)
Peter Alspach wrote:
> Tena korua David and Jon
>
> Without an Error() in the model, you get standard errors for the effects
> and standard errors of the difference for the means. With fully
> balanced data, as in the example, these are directly comparable (compare
> model.tables(npk.aov, se=T)*sqrt(2) with model.tables(npk.aov,
> type='means', se=T)$se). For data with uneven replication this will not
> be the case.
>
> The standard errors of the differences for the means is not yet
> implemented for aovlist (which is returned with an Error() in the model
> as in npk.aovE). I imagine this is because of the issues that arise in
> comparing means from different strata.
>
> HTH .....
>
> Peter Alspach
>
>
>> -----Original Message-----
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of David Winsemius
>> Sent: Wednesday, 23 December 2009 4:13 p.m.
>> To: Jon Prince
>> Cc: r-help@r-project.org
>> Subject: Re: [R] trouble with model.tables SE means
>>
>>
>> On Dec 22, 2009, at 8:52 PM, Jon Prince wrote:
>>
>>
>>> David Winsemius wrote:
>>>
>>>> On Dec 22, 2009, at 5:19 PM, Jon Prince wrote:
>>>>
>>>>> David Winsemius wrote:
>>>>>
>>>>>> On Dec 22, 2009, at 4:22 PM, Jon Prince wrote:
>>>>>>
>>>>>>
>>>>>>> Hi, I'm new to R, with some experience with Matlab and SPSS.
>>>>>>> I've figured out how to run my repeated measures anova and am
>>>>>>> getting the right numbers for my effects (comparing
>>>>>>>
>> with results
>>
>>>>>>> from other software), but am having trouble with the
>>>>>>>
>> model.tables
>>
>>>>>>> function. Specifically, using:
>>>>>>>
>>>>>>> prints the means, but then won't do the SE values,
>>>>>>>
>> instead giving:
>>
>>>>>>> Warning message:
>>>>>>> In model.tables.aovlist(fm, "means", se = TRUE) :
>>>>>>> SEs for type 'means' are not yet implemented"
>>>>>>>
>>>>>>> Asking for SEs for "effects" works fine, but that's not what I
>>>>>>> want. I searched the help for this issue and one other
>>>>>>>
>> person has
>>
>>>>>>> had this problem last year
>>>>>>>
>>>>>>>
>> (http://markmail.org/message/k5yxxqcfiihvzvtp?q=list:r-project+mod
>>
>>>>>>> el%2Etables ), but the person helping them was unable
>>>>>>>
>> to replicate
>>
>>>>>>> it, inferring that it was an out-of-date version. My version is:
>>>>>>>
>>>>>>> R version 2.10.1 (2009-12-14)
>>>>>>>
>>>>>>> I only downloaded it the other day, and therefore
>>>>>>>
>> cannot have an
>>
>>>>>>> outdated version. How can I fix this error and get my SE values?
>>>>>>> Apologies if I have not provided sufficient information, and
>>>>>>> thanks in advance for your help.
>>>>>>>
>>>>>> When I look at the output of the first model.tables call copied
>>>>>> from the help page, I see a list element that holds "se" values.
>>>>>> Try:
>>>>>>
>>>>>> model.tables(fm,"means",se=TRUE)$se
>>>>>>
>>>>>>
>>>>> Thanks for the rapid reply! Unfortunately adding the $se returns
>>>>> NULL, and repeats the same warning message ("...not yet
>>>>> implemented"). If you're not experiencing the issue, is
>>>>>
>> it possible
>>
>>>>> for me to replace the relevant code/source file with what
>>>>>
>> you have
>>
>>>>> (or would that require recompiling)? Could this be an OS
>>>>>
>> issue? I'm
>>
>>>>> running Mac OSX 10.6.2.
>>>>>
>>>>> By the way, I "replied all" on this message, but let me
>>>>>
>> know if that
>>
>>>>> is not the preferred convention. Cheers,
>>>>>
>>>> Reply all. That way people can correct my mistakes and general
>>>> cluelessness. I'm running MacOSX 10.5.8 so it would seem
>>>>
>> less likely
>>
>>>> that is the explanation.
>>>>
>>>> 1) Did you run the example in the help pages?
>>>>
>>>> 2) When I look at :
>>>>
>>>>
>>>>> methods(model.tables)
>>>>>
>>>> [1] model.tables.aov* model.tables.aovlist*
>>>>
>>>> ... I see both an "aov" method and an "aovlist" method. Is it
>>>> possible that there is something about the object that you are
>>>> working on that makes it an aovlist at thus invokes a different
>>>> function than what the help page invokes?
>>>>
>>>> The code would not require complination... it's available with
>>>> getAnywhere() and I do not see any calls to compiled or .Internal
>>>> subroutines. Tell me what happens with the above questions first.
>>>>
>>>>
>>> Sorry for the delayed response, I've been trying to work out the
>>> discrepancy between my data and the example data in terms
>>>
>> of getting
>>
>>> the SE means.
>>>
>>> 1.) Upon trying the example, it appears to work on my
>>>
>> machine (i.e., I
>>
>>> get the SE means). Since then I've been spending my time trying to
>>> figure out why it doesn't do the same for my data. I can't
>>>
>> figure it
>>
>>> out.
>>>
>>> 2.) Given my lack of experience, it is quite possible that
>>>
>> I've loused
>>
>>> up an object somewhere, but I don't know how to track that down. I
>>> have put my code below, and can send the data file too if you're
>>> willing to take a look. Both the p and t factors have three levels,
>>> combined factorially. There are four replications of each p- t
>>> combination, and the rating data vary from 1 to 7.
>>>
>>> ##load data
>>> rate_data<-read.table("/Users/jonprince/Desktop/
>>> attend_pitch_3p3t.txt")
>>> ##set factors
>>> p<-factor(rate_data$V3)
>>> t<-factor(rate_data$V2)
>>> subject<-factor(rate_data$V1)
>>> ##set data
>>> rate<-rate_data$V4
>>> ##run anova
>>> fm<-aov(rate ~ p*t + Error(subject/(p*t)),rate_data)
>>>
>> But, but, but, ... none of those objects (p,t,subject, rate)
>> are part of rate_data!
>>
>>
>>> ##get summary
>>> summary(fm)
>>> ##tables
>>> model.tables(fm,"means",se=TRUE)
>>>
>> Without more information, I would be flailing around, and
>> even then I am not particularly experienced with the aov
>> framework. My guess is that you will get better advice on the
>> R-mixed-models-SIG. I would offer more information to that
>> group, at a minimum the output of str on rate_data (once you
>> actually create the variables IN rate_data.)
>>
>> --
>> David
>>
>>> Thanks again, I really appreciate the help.
>>>
>>> Jon
>>>
>>>
>>> --
>>> Jon Prince
>>> Postdoctoral Research Associate
>>>
>>>
>>>
>> David Winsemius, MD
>> Heritage Laboratories
>> West Hartford, CT
>>
>> ______________________________________________
>> 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.
>>
>>
>
>
>
--
Jon Prince
Postdoctoral Research Associate
Department of Psychology
356 Park Hall
University at Buffalo, SUNY
Buffalo, NY 14260
office (716) 645 0235
lab (716) 645 0225
home (716) 839 1315
jonpr...@buffalo.edu
http://www.acsu.buffalo.edu/~jonprinc/
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