[R] model.tables error from aov

[John Vokey]

In addition, your model statement is odd.  Note that within-S factor  
Type is tested with both the type I and the type II residuals, whereas  
only the latter should be used.  Try this model instead:

aov.errs.ae <- aov(TrainErrs ~ idio*Type + Error(Subject/ 
Type),data=learnDat.ae)

or, for more clarity:

aov.errs.ae <- aov(TrainErrs ~ idio*Type + Error(Subject 
+Subject:Type),data=learnDat.ae), which explicitly denotes the two  
error strata.

On 17-Dec-08, at 4:00 AM, r-help-request at r-project.org wrote:

> Your design seems to be unbalanced: multistatum aov is intended for
> balanced designs.  My guess is that one idio subject has two Type=1
> observations: in which case try removing one of them.
>
> On Tue, 16 Dec 2008, Harlan Harris wrote:
>
>> Hi, I'm a new R user, coming from SPSS, and without a particularly  
>> strong
>> stats background.
>>
>> I've got a data set that I'd like to do a mixed-design ANOVA with. No
>> missing values. Here's the summary:
>>
>> summary(learnDat.ae)
>> Type      Subject        idio     struct     TrainErrs             
>> cond
>> 0:20   11     : 3   idio   :28   ae  :58   Min.   : 0.00    
>> idioae   :28
>> 2:19   12     : 3   nonidio:30   fact: 0   1st Qu.: 6.25    
>> idiofact : 0
>> 3:19   14     : 3                          Median :11.50    
>> nonidioae:30
>>       15     : 3                          Mean   :13.40
>>       18     : 3                          3rd Qu.:16.00
>>       2      : 3                          Max.   :59.00
>>       (Other):40
>>
>> Note that the TrainErrs column is the only numeric column, and I  
>> forced
>> everything else to be a factor. (Is that correct?)
>>
>> I then do the following:
>>
>> aov.errs.ae <- aov(TrainErrs ~ (idio*Type) + Error(Subject/Type) +  
>> (idio),
>> learnDat.ae)
>>
>> So, idio is between-subjects and Type is within-subjects. This is  
>> based on
>> examples I've found elsewhere.
>>
>> summary(aov.errs.ae)
>>
>> This seems to work fine:
>>
>> Error: Subject
>>         Df Sum Sq Mean Sq F value Pr(>F)
>> idio       1    179     179    0.89   0.36
>> Type       1    210     210    1.05   0.32
>> Residuals 17   3401     200
>>
>> Error: Subject:Type
>>         Df Sum Sq Mean Sq F value Pr(>F)
>> Type       2    515     258    2.44  0.103
>> idio:Type  2    680     340    3.22  0.053 .
>> Residuals 34   3595     106
>> ---
>> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>>
>

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-Dr. John R. Vokey