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

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

Subject |
Re: st: RE: st: C-statistic with -gologit2- |

Date |
Wed, 07 Oct 2009 14:58:42 -0500 |

At 01:30 PM 10/7/2009, Newson, Roger B wrote:

In the case of ordinal regression, instead of using the predictedprobability, you should use the linear predictor, computed using-predict- with the -xb- option. This linear predictor is an ordinalpredictor of the outcome. It then makes sense to use thec-statistic, although the confidence intervals should only be takenseriously if calculated (using out-of-sample prediction) in adifferent dataset from the dataset in which the ordinal model was fitted.

In the case of mlogit, there are multiple linear predictors,interpreted as the log odds ratios (per X-unit) of the variousnon-baseline outcomes compared to the baseline outcome. In thatcase, the c-statistic for the linear predictor for each non-baselineoutcome only makes sense if restricted to observations with eitherthat non-baseline outcome or the baseline outcome.

------------------------------------------- Richard Williams, Notre Dame Dept of Sociology OFFICE: (574)631-6668, (574)631-6463 HOME: (574)289-5227 EMAIL: Richard.A.Williams.5@ND.Edu WWW: http://www.nd.edu/~rwilliam * * 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**:**RE: st: RE: st: C-statistic with -gologit2-***From:*"Newson, Roger B" <r.newson@imperial.ac.uk>

**References**:**st: C-statistic with -gologit2-***From:*s.muller@cphc.keele.ac.uk

**Re: st: C-statistic with -gologit2-***From:*Jeph Herrin <junk@spandrel.net>

**Re: st: C-statistic with -gologit2-***From:*Richard Williams <Richard.A.Williams.5@ND.edu>

**st: RE: st: C-statistic with -gologit2-***From:*"Newson, Roger B" <r.newson@imperial.ac.uk>

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