logistic regression - exp(estimates)?

hello.

I have a question on the interpretation of a logistic model.

is it helpful to exponentiate the coefficients (estimates)? I think I
once read something about that, but I cannot remember where.
if so, how would be the interpretation of the exp(estimate) ?

exp(beta_i) is the odds ratio for success when the i-th predictor
	x_i is incremented by 1.

	In particular if x_i is a 0-1 indicator variable then exp(beta_i) is
	the odds ratio for comparing the odds of success when x_i = 1 with
	the odds of success when x_i = 0.

	E.g. if x_i = 0 for Male and x_i = 1 for Female, and exp(beta_i) = 2,
	then the odds of success for Females are twice as great as the odds
	of success for Males.  I.e. Females are ``twice as likely'' to succeed
	as Males, all other things being equal.  (Which may or may not be a  
Good
	Thing, depending on what ``success'' really means. :-) )

would there be a change of the interpretation of the ANOVA table  
(or is
the ANOVA table not really helpful at all?).

ANOVA tables are ***so*** 20th century!

		cheers,

			Rolf Turner

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