http://spssx-discussion.165.s1.nabble.com/wilk-s-lamda-tp4729461p4735949.html
Scott,
I was never so gung-ho about logistic as some other people
"... [R]esults are easier to interpret" is not my experience.
I find mean-differences between groups and simple regression-
type coefficients easy to grasp, in comparison to dealing with
odds-ratios and Log-odds. I like the ancillary statistics that are
typical with DFA (and not with LR).
LR has a theoretical advantage that seldom makes a practical difference.
There is a trade-off for absorbing certain outliers -- logistic regression
is less robust at small Ns. Also, LR induces users to ignore the fact
that the immediate result is supposed to be a well-behaved
linear equation -- which suggests to me, immediately, that I want
predictor variables that are pretty well-scaled and well-behaved.
Users of LR are not issued a free pass on these issues, despite
any proclamation of "less restrictive." - I suppose what I *dislike*
about LR is mainly that its users seem to be encouraged to be
careless, whereas users of multiple regression and DFA are
encouraged to worry about assumptions.
--
Rich Ulrich
Date: Thu, 25 Aug 2011 12:16:50 -0700
From:
[hidden email]Subject: Re: wilk's lamda
To:
[hidden email]Why
didn't you use logistic regression instead of DFA? Logistic regression
has fewer restrictive assumptions than DFA---and the results are much
easier to interpret.
~~~~~~~~~~[snip]