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# Re: st: Xtmixed specification for rmANOVA with 2 within-subject factors

 From Jared Saletin <[email protected]> To [email protected] Subject Re: st: Xtmixed specification for rmANOVA with 2 within-subject factors Date Wed, 6 Apr 2011 22:54:37 -0700

```Hi Dave,

Thanks again!

I found the linked thread most illuminating and helpful, especially the discussion of how error in a rmANOVA can either be conceptualized as separate terms for each factor, or modeled as simply the residual. This difference I think accounts for the discrepancies I've noticed.

Thanks again,
Jared

On Apr 6, 2011, at 7:35 AM, Airey, David C wrote:

> .
>
>> Hi Dave,
>>
>> Thanks for the response!
>>
>> And thanks for the tip on anovalator! I've recently started using it, and very much enjoy it!
>>
>> I do have the book you mention, and have found it particularly useful in expanding my understanding of LMMs.
>>
>> I'm still finding myself having a remaining issue though.
>>
>> In the book, the rat-brain example would suggest that with two within-subject factors a model such as this would suffice :
>>
>> xtmixed y  b##c | s:, var
>>
>> --
>>
>> I was mainly then confused by the UCLA page here:
>>
>>
>> http://www.ats.ucla.edu/stat/stata/faq/margins_mixed_anova.htm
>>
>>
>> Where for a split-plot design with two within-subject factors (along with a between-subject factor) the authors use the crossed-random factor model:
>>
>> e.g.  xtmixed y a##b##c || _all: R.bs || _all: R.cs || _all: R.bcs || s:, var
>>
>> I'm mainly confused as to why in this instance of a split-plot (with 2 within subject factors), but neither in the rat-brain totally within-subjects example from the book nor the first split-plot model presented on the UCLA page (1 between subject factor, 1 witihin-subject factor), are the the within-subject factors now considered crossed random-effects.
>>
>> I haven't been able to reconcile the different approaches, even after reading the chapter from the book.
>>
>> Thanks again!
>> Jared
>
> I think this has come up before on Statalist, and has to do with conceptualization of the rmANOVA model.
>
> <http://www.stata.com/statalist/archive/2010-03/msg01340.html>
>
> It is a good question for the authors of that book, or tech-support at Stata Corp.
>
> -Dave
>
>
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```