Austin Nichols has kindly pointed out that what I wrote below is not
correct as a summary of what was in the article. See the article itself
for the story. Thanks to Austin for the quick fix.
-----Original Message-----
From: Nick Cox
Sent: 04 September 2008 17:50
To: '[email protected]'
Subject: FW: st: RE: Dependent var is a proportion, with large spike in
.95+
A formal statement can be found within
http://www.stata-journal.com/sjpdf.html?articlenum=gr0010
together with explicit code for exploring the question graphically.
Whatever the parameters, the result of a logit transform of a beta
distribution is a logistic distribution, which is bell-shaped.
Of course, real datasets might not be so well behaved, as I presume all
agree.
Nick Cox
Jverkuilen
#A good approximation is if that you take #logits of a beta-distributed
#variable, the distribution looks bell-
#shaped. That's true even for
#highly skewed betas with modes near 0 #or near 1.
Yes, so long as the distribution is not J- or L-shaped, which can happen
with the beta. It can handle those shapes and endpoint bimodality too.
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