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From |
Jay Kaufman <Jay_Kaufman@unc.edu> |

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

Subject |
st: -binreg- |

Date |
Thu, 21 Nov 2002 13:28:10 -0500 |

The -binreg- routine fits generalized linear models for the binomial family. It is presumably preferred over fitting the same model in -glm-, not only for the convenience of not having to specify the distributional family in the command line, but also because in iteratively seeking the estimates it checks to make sure that they are consistent with the range of allowable probabilities (i.e. 0 to 1), as described on page 138 of the manual [Ref A-G]. So my question is, why does -binreg- appear to be so bad at this checking? Take a very simple model using the auto.dta. . use "C:\Stata\auto.dta", clear (1978 Automobile Data) . binreg foreign mpg, rr Residual df = 72 No. of obs = 74 Pearson X2 = 73.88014 Deviance = 78.99933 Dispersion = 1.026113 Dispersion = 1.097213 Bernoulli distribution, log link ---------------------------------------------------------------------- | EIM foreign | Risk Ratio Std. Err. z P>|z| [95% Conf. Interval] --------+------------------------------------------------------------- mpg | 1.097213 .0109901 9.26 0.000 1.075883 1.118966 ---------------------------------------------------------------------- . predict phat, mu . sum phat Variable | Obs Mean Std. Dev. Min Max -------------+----------------------------------------------------- phat | 74 .3008965 .22691 .1072727 1.580984 Clearly a predicted probability > 1.5 is not a good estimate. Did I do something wrong? Or did -binreg- do something wrong? Or is this simply another example of why linear models of the logit and probit have dominated analysis of binary data for decades? By the way, note that if I fit the exact same model using -glm-, this same observation gets a predicted probability of 1.43, so -binreg- actually seems to do worse. -- Jay S. Kaufman, Ph.D ----------------------------- email: Jay_Kaufman@unc.edu ----------------------------- Department of Epidemiology UNC School of Public Health 2104C McGavran-Greenberg Hall Pittsboro Road, CB#7435 Chapel Hill, NC 27599-7435 phone: 919-966-7435 fax: 919-966-2089 ----------------------------- * * 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/

**Follow-Ups**:**st: RE: -binreg-***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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