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Topic: one-way repeated measures ANOVA with more levels than subjects
Replies: 8   Last Post: Nov 6, 2013 3:53 AM

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Art Kendall

Posts: 200
Registered: 12/7/04
Re: one-way repeated measures ANOVA with more levels than subjects
Posted: Oct 23, 2013 1:39 PM
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I do not know what the software other than SPSS was, but you may want to
check with a discussion list for that software. My guess is that you
did not use specifications that said you had repeated measures.

I can think of no reason that you cannot have more levels of repeat than
number of cases.

Times series is a particular kind of repeated measure and economists
routinely use a single case.

BTW color can be a nominal level variable but it can also be thought of
an array along a spectrum ROYGBIV, so you depending on exactly what you
have for color stimuli you may be able to put structure on your repeats.

What syntax did you use in SPSS?

Art Kendall
Social Research Consultants

On 10/23/2013 12:48 PM, Tim wrote:
> Hi everyone,
>
> I have a quick question about a one-way repeated measures ANOVA in cases where the number of levels in a factor is larger than the number of subjects measured. Let me illustrate my question with a quick example: Say we presented 20 different colors in an experiment and recorded reaction times for every condition in 15 subjects (a total of 20*15=300 measurements). To my understanding, as we have 15 within-subject measurements for every cell, this should work perfectly fine.
>
> Unfortunately, two of the statistics functions we tried using throw an error stating that the number of conditions is too large given the number of subjects (one seems to directly compare the two numbers, the other one computes negative df_error). However, the same kind of setting works just fine in SPSS (df1 = 19; df2 = 266).
>
> Is there any principled reason why above setting should be problematic in a repeated-measures ANOVA? My search for an explanation has so far not brought up any reason why the number of levels in a factor should not exceed the number of subjects if all observations have been measured (n_obs = n_sub * n_cond).
>
>
> Thanks a lot in advance, looking forward to your answers
> Tim
>




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