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Community Manager
Hi @Reinaldo,
As others have pointed out you have the option to analyze these data in a few different ways, a MANOVA (which is also where you will find univariate adjusted and unadjusted repeated measures), or a linear mixed effects model. To produce the Mauchly's Test of Sphericity, you will need to use the MANOVA personality in Analyze > Fit Model. For this, as you noticed, you will be using your data in wide/split form (dataset attached with script). Here's the set up in Fit Model:
Then, in the MANOVA report, you will want to construct a response specification: Click "Choose Response" and select "Repeated Measures," and also check box for Univariate tests. Title your within-subject factor as you like:
At the bottom of the report you will see your tests of the within-subject effect, as well as the Mauchly's Test of Sphericity. You can also specify other contrasts if you wish here, but you might enjoy the interface more when using a mixed model approach.
To fit these data using a mixed model, first stack you data (dataset attached). Next, launch Analyze > Fit Model, and place your response as Y. Next, place your subject column as well as label (or whatever you called your factor when you stacked) in as model effects. Select Subject in the model effects, then click the red triangle next to attributes, and select Random. Subject MUST be marked as nominal in your data table otherwise this will return an incorrect analysis. You do not need to use Nest in this case -- subjects would only be nested inside of a between-subject variable, and in this example you have none.
When you click Run, you will get what is an equivalent analysis (since you have no missing data) to the univariate unadjusted analysis output you found from the MANOVA personality.
However, one benefit of using this modeling personality is that the Red Triangle next to your factor (label in this case) has additional useful options, such as performing all pairwise comparisons, Tukey-HSD, and custom single and multi-degree of freedom contrasts using a simple control panel.
To fit more complicated repeated measures models, you might check out the Full Factorial Repeated Measures Add-in, which also works for one-way repeated measures such as this, but as you can see these are not too difficult to set up.
I hope this helps!
Use
Tables==>Stack
to put all of your test columns into a single column, and then run
Analyze==>Fit Model
and setup the dialog box like
