Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down on April 23, and its replacement, **statalist.org** is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
"Rourke O'Brien" <rourke.obrien@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: oglm and heterogeneous choice models |

Date |
Mon, 24 Oct 2011 14:12:14 -0400 |

I have a follow up question on heterogeneous choice models. I am interested in testing which variables significantly predict residual variance. I’ve tried many configurations of the “sw, pe(.05): oglm y x1 x2 x3 x4, eq2(x1 x2 x3 x4) flip” but have not been able to achieve convergence. Yet, when I use the gologit2 command and the autofit option, the model runs smoothly and I am told which covariates do not meet criteria for parallel line assumptions. I can then run the model using gologit2 and specify which predictors meet the parallel line assumptions and which do not. Is this an appropriate strategy? I am ultimately interested in testing for an interaction in a logistic model. Thanks for any assistance! On Mon, Oct 24, 2011 at 1:04 PM, Rourke O'Brien <rourke.obrien@gmail.com> wrote: > > I have a follow up question on heterogeneous choice models. > > I am interested in testing which variables significantly predict residual variance. I’ve tried many configurations of the “sw, pe(.05): oglm y x1 x2 x3 x4, eq2(x1 x2 x3 x4) flip” but have not been able to achieve convergence. Yet, when I use the gologit2 command and the autofit option, the model runs smoothly and I am told which covariates do not meet criteria for parallel line assumptions. I can then run the model using gologit2 and specify which predictors meet the parallel line assumptions and which do not. Is this an appropriate strategy? I am ultimately interesting in analyzing the effect of an interaction in a logistic model. Thanks for any assistance! > > On Sat, Jul 23, 2011 at 6:09 PM, Richard Williams <richardwilliams.ndu@gmail.com> wrote: >> >> At 03:33 PM 7/23/2011, Rourke O'Brien wrote: >>> >>> I am currently running logit models predicting success (dichotomous) >>> with sex and income as main predictors. I understand that with >>> potential unequal variances across groups I should explore >>> heterogeneous choice models. See: >>> http://www.nd.edu/~rwilliam/oglm/RW_Hetero_Choice.pdf >> >> Incidentally, since success is dichotomous, you could also use -hetprob-. It will (hopefully) give the same results as oglm with link(probit). But (somewhat to my annoyance) I have found that official Stata commands tend to be way faster than my commands are when estimating the same models. >> >> >> ------------------------------------------- >> 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/ > * * 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/

- Prev by Date:
**Re: st: R: variable not found?** - Next by Date:
**Re: st: R: variable not found?** - Previous by thread:
**st: RE: FE over two columns** - Next by thread:
**Re: st: oglm and heterogeneous choice models** - Index(es):