There is a literature on "compositional data" which probably will be helpful.
Years ago, I found Aitchison to be readable.
I have no idea whether it will work for your model, but I will mention
that you escape the absolute linear dependency if you represent each
fraction as its log-odds, like log(25/75) in place of 25%.
--
Rich Ulrich
Date: Thu, 4 Apr 2013 12:05:47 +0400
From:
[hidden email]Subject: Repeated measures analysis of fractions summing to a constant
To:
[hidden email]
Consider you have a between-within design: several between-subject
groups and several (3 or more) repeated measures (= within-subject)
trials. It's all very classic and typical. The nuance, however, is
that the values for every subject sum across the repeated levels to
a **constant**. This is because the data are complementary, i.e.
percentages of fractions, so, in this case they sum to 100 for every
individual. For example, with 3 RM levels, a respondent's data is
like 30%, 22%, 48% (sum=100); for another respondent 25%, 33%, 42%
(sum=100).
I know that I can analyze between-groups X repeated-measures count
data via Generalized Estimating Equations procedure. By I doubt in
this case because the values *sum to a constant*, they are
complementary fractions; they are not counts of successes in
repeated independent trials!
Can I analyze such data in SPSS and how? Thanks.