This is discussed in Buis (2007) "predict and adjust with logistic
regression", The Stata Journal, 7(2), pp. 221-226.
http://www.stata-journal.com/article.html?article=st0127
The reason for the difference is that -logit- implies a non-linear
transformation, so it makes a difference whether you first create
predicted values and than compute the mean, or when you first compute
the means of explanatory variables and than compute a predicted value.
To quote from the article: "It is the difference between a typical
predicted probability for someone within a group and the predicted
probability for someone with typical values on the explanatory
variables for someone within that group."
Hope this helps,
Maarten
--- Jn <[email protected]> wrote:
> I am trying to get at the magnitude of a change in Pr(y=1|x) by
> replacing each explanatory variable with its sample average, save for
> my variable of interest, which I was hoping to use a future projected
> distribution (I'm trying to see how this change in distribution of
> this certain binary independent variable changes the probability of
> y=1). I had no problem doing this with linear regressions (replace
> all
> variables with its sample mean, except use projected distribution for
> my variable of interest, do a linear prediction, note the
> difference).
> However, when I try to carry out the same procedure in a logit
> regression, I am running into problems. I was under the impression
> that, if I were to replace ALL of my independent variables with its
> sample mean and then run -predict-, I should get the same predicted y
> value as if I were to just run a normal regression without replacing
> my x-var with its sample mean. Am I wrong? I hope I am making myself
> clear..
-----------------------------------------
Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting address:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
-----------------------------------------
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