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st: re: marginal vs discrete effects in logistic regression


From   Kouji Asakura <asakura.koji@yahoo.com>
To   statalist digest <statalist@hsphsun2.harvard.edu>
Subject   st: re: marginal vs discrete effects in logistic regression
Date   Wed, 3 Aug 2011 22:25:54 -0700 (PDT)

Dear Statalisters,


I would just like to ask something regarding the interpretation of logistic regression coefficients in terms of effect on the probabilities of success instead on the logit

1) In trying to compute for the marginal effects, i came across two commands in stata that compute for these : prchange and mfx.  From what I have read so far, mfx computes for the change in probability for every increase in your independent variable, while holding the other variables constant at their mean, while for the marginal effects computed by the prchange command, it is described as "MargEfct: the partial derivative of the predicted probability/rate with respect to a given independent variable". My question however is... are these marginal effects applicable if all of your predictor variables are discrete/ at most ordinal scale? I'm hesitant to interpret the marginal effects as "change in probability... while holding other variables constant at their mean" because ordinal variables do not have means. 


2). I am computing the marginal effects also for the purpose of determining the variable's order of influence on the probability of success (which variable has the most influence, has the least, etc) ... but when I compare them with the standardized coefficients, the rankings differ... Which is the more appropriate statistic to use for this purpose?

I really hope you guys can shed light on these problems. Thank you very much in advance.


Best regards,

Kohji Asakura

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