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From |
Richard Williams <Richard.A.Williams.5@ND.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: logistic ---- assessment of model fit via external validation |

Date |
Wed, 09 Jun 2004 13:49:15 -0500 |

At 12:06 PM 6/9/2004 -0600, cthompson@dfpm.utah.edu wrote:

Incidentally, my own inclination, quite possibly wrong, would be to test whether parameters significantly differed between my 2 samples. Building on my previous example, you could do that via a Chow test procedure, something likeHello All --- I'm using Intercooled Stata, 8.2. In Hosmer & Lemeshow's "Applied Logistic Regression", the authors indicate that it may be possible to exclude a subsample of observations, develop a model, then test the model on the excluded observations (p.171). I'm interested in doing just that, although I'm at a loss as to if -- and how -- something like this can be implemented in Stata. I've searched the Statalist archives,

. xi: quietly logit foreign price i.mysample i.mysample*price

i.mysample _Imysample_0-1 (naturally coded; _Imysample_0 omitted)

i.mysam~e*price _ImysXprice_# (coded as above)

. test _Imysample_1 _ImysXprice_1

( 1) _Imysample_1 = 0

( 2) _ImysXprice_1 = 0

chi2( 2) = 1.36

Prob > chi2 = 0.5075

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**References**:**st: logistic ---- assessment of model fit via external validation***From:*<cthompson@dfpm.utah.edu>

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