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From |
Jn <[email protected]> |

To |
[email protected] |

Subject |
st: computing average partial effect in nonlinear models using forecasted distribution of x-variables |

Date |
Tue, 25 Mar 2008 06:47:53 -0400 |

Dear Statalisters, 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.. Any help would be greatly appreciated. Thanks, * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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