Xiaoqiang Cheng:
You are fitting a nonlinear curve, so the effect of x changes as x changes. See for instance slide 21 in my presentation. With -mfx- you are summarizing this with one number, so you are approximating this non-linear curve with a straight line. In other words you are estimating the effect of a unit change for an average individual (default), or an individual with the values of x you specified. If the unit of your x is pretty small this approximation is usually fine, but if it is large you get strange results like you have just shown. -mfx- won't standardize the explanatory variable for you, so if you haven't standardized the variable uba, than -mfx- will show you the effect of a unit change, where the unit is the original unit in your dataset. The solution is to choose a smaller unit, for instance by dividing uba by some number (10 or 100) to improve the approximation.
HTH,
Maarten
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Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z434
+31 20 5986715
http://home.fsw.vu.nl/m.buis/
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-----Original Message-----
From: [email protected] [mailto:[email protected]]On Behalf Of Cheng, Xiaoqiang
Sent: maandag 2 oktober 2006 11:44
To: [email protected]
Subject: st: RE: st: ´ð¸´: st: How to choose a proper model if the dependent variable is within bounds?
However, there is a problem now:
-mfx- predicts that:
variable | dy/dx Std. Err. z P>|z| [ 95% C.I. ] X
uba| -3.05144 1.55749 -1.96 0.050 6.10406 .001175 .004839
And the effect of uba on dependent variable exceeds unit if one std. dev. Of uba changes, certirus paribus?
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