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From |
jhilbe@aol.com |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: RE: curious behavior of glm |

Date |
Fri, 05 Jun 2009 12:09:22 -0400 |

y n x -------------- 10 100 1 0 100 0 Model the above using -exlogistic-: . input r n x r n x 1. 10 100 1 2. 0 100 0 3. end . exlogistic y x, binomial(n) coef estc Enumerating sample-space combinations: observation 1: enumerations = 11 observation 2: enumerations = 101 observation 3: enumerations = 10201 note: CMLE estimate for x is +inf; computing MUE note: CMLE estimate for _cons is -inf; computing MUE note: .975 quantile estimate for _cons failed to bracket the value

------------------------------------------------------------------------- --

-------------+----------------------------------------------------------- --

------------------------------------------------------------------------- -- (*) median unbiased estimates (MUE)

. glm r x, fam(bin n)

Variance function: V(u) = u*(1-u/n) [Binomial] Link function : g(u) = ln(u/(n-u)) [Logit]

----- | OIM

-----

-----

. di %12.0f exp(23.87722) 23428521860 We have an odds ratio here of some 23.4 billion. No surprise.

The bottom line is that there is nothing wrong with -glm- here. Joseph Hilbe * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: RE: curious behavior of glm***From:*"Mak, Timothy" <timothy.mak07@imperial.ac.uk>

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