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: [email protected]
>> [mailto:[email protected]] On Behalf Of David Winsemius
>> Sent: Wednesday, 23 December 2009 4:13 p.m.
>> To: Jon Prince
>> Cc: [email protected]
>> 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
>>
>> ______________________________________________
>> [email protected] 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
[email protected]
http://www.acsu.buffalo.edu/~jonprinc/
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