To use proportion (percentage) data as a dependent
variable in a regression, you would need to transform
the data before doing regression for two purposes: to
confine the projected value within 0-1 and to make the
data distribution closer to normal. I have read a
description on stata Q&A about using logistic
transformation for proportion (percentage) data
(y=ln(x/(1-x)) and it seems working fine. However,
recently, I read about another highly recommendated
transformation method for percentage data, arcsine
transformation: (y=sine(x)^-1). Can anyone tell me
about the pros and cons of these two methods for
transforming proportion (percentage) data, and which
one should be used for what situation?
Mark Xu
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