Viktor Slavtchev wrote:
>>I have individual data where people report the share of time they
spend
in five distinct activities. People can do more than one activity every
day: first jogging, then go to work, then shopping, whatever. That is,
there are five observation per ID individual. Actually, the ID is the
(each person's) day. I wish to explore the individual characteristics
determining the share of time spent for each activity.
As the dependent variable is a share [0;1] I was thinking about
fractional logit. In Stata it would be (I guess):
glm y x, family(binomial) link(logit).
However, I am not clear whether fractional logit can be applied on the
original data, or the data have first to be transformed in some way.
Moreover, in doing -glm- live above I implicitly assume that each
observation is independent which is definitely not true.
Does anybody know some solution?<<
Yes, you are correct that there are notable dependencies among the
variables caused by the sum constraint. Take a look at the book by John
Aitchison, Compositional Data Analysis. The original edition is 1986 but
it was republished in 2003 with some additions.
Feel free to drop me a line, I'm interested in this problem.
Jay
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