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From |
"Auh, Jun Kyung" <jauh14@gsb.columbia.edu> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
st: Interpretation of Cut Points in Ordered Probit (Logit) Model |

Date |
Thu, 25 Apr 2013 21:25:16 -0400 |

Hi All- I am having a hard time to give an interpretation on the cut off points in ordered probit regression. Suppose that I have the following structure: The latent variable Z is linear in observable variable X: Z = b*X + u , u~N(0,1) The resulting (observable) variable takes 3 values: Y = 3 if Z > cut1 Y = 2 if cut2<Z<cut1 Y = 1 if cut2>Z X variable has non-zero value and Y is distributed in normal way in the data (say Y = 1 is 20%, Y = 2 is 60% and Y =3 is 20%) The regression results show that I have negative value for cut2. If cut2 < 0, wouldn't the model predict that there is zero observation with Y = 1? Or, is the cut points are de-meaned? i.e, do I have to add back the mean of X to have correct interpretation? Any help would be greatly appreciated! Best, JK * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Interpretation of Cut Points in Ordered Probit (Logit) Model***From:*"JVerkuilen (Gmail)" <jvverkuilen@gmail.com>

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