Notice: On March 31, it was **announced** that Statalist is moving from an email list to a **forum**. The old list will shut down at the end of May, 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 |
Tue, 25 Oct 2011 13:15:15 -0400 |

Thanks so much for the follow up! Yes the DV is dichotomous. Does the Brant test work for dichotomous variables? I kept getting errors that there had to be multiple levels (ordinal). And I was using the lr option as well, just forgot to mention. If I use gologit2 to identify problematic variables can I also use it to estimate a model that corrects for the hetero (by denoting which vars meet the pl assumption and which do not)? Or do I need to use that information and run the model in oglm? And I completely agree that its best to find other ways to tweak the model to deal with the hetero as these models are certainly tricky! External readers pushing to test it both ways. On Mon, Oct 24, 2011 at 7:19 PM, Richard Williams <richardwilliams.ndu@gmail.com> wrote: > At 01:12 PM 10/24/2011, Rourke O'Brien 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 interested in testing for an interaction in a logistic >> model. > > Is the dv dichotomous? These models can be difficult to estimate as is, and > are even tougher with a dichotomous dv. > > The oglm help recommends using the -lr- option of -sw-. The default -wald- > option gets confused when the same variable is in both the variance and > choice equations, i.e. it tests the variable in both equations when you only > want it tested in the variance equation. > > Either a brant test or gologit2 can identify variables that are problematic. > You can try including those variables in the variance equation of a hetero > model -- it may or may not work well. > > Even though I programmed oglm to support sw, I am not crazy about its use. > In my Stata Journal article (Stata Journal 10(4):540-567) I suggested you > think of this as being like a diagnostic test. If the assumption of > homogeneous errors seems to be violated, think about other ways to solve the > problem, e.g. add a variable, add a squared term. I make the same advice for > OLS models where hetero seems to be a problem -- see if there is some > reasonable way to make the hetero go away by tweaking your model. > > > ------------------------------------------- > 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/

**References**:**Re: st: oglm and heterogeneous choice models***From:*Richard Williams <richardwilliams.ndu@gmail.com>

- Prev by Date:
**Re: st: proportional random sampling** - Next by Date:
**Re: st: proportional random sampling** - Previous by thread:
**Re: st: oglm and heterogeneous choice models** - Next by thread:
**Re: st: oglm and heterogeneous choice models** - Index(es):