Re: st: oglm and heterogeneous choice models

[Richard Williams <richardwilliams.ndu@gmail.com>]

At 02:55 PM 10/25/2011, Rourke O'Brien wrote:
> Gotcha. That makes sense. I was trying to find another way to diagnose
> which variables predict residual variance since using "sw, pe(.05) lr:
> oglm y x1 x2 x3 x4 , eq2(x1 x2 x3 x4) flip" wont converge unless I
> reduce the model and use fewer predictors.
>
> The gologit2 results do indeed mirror the logit results. I was just
> wondering if I could use gologit2 to see what variables would be
> problematic.
Not with a dichotomous dv. And given that it is a dichotomous DV you 
could just use hetprob, which is probably faster than oglm and may be 
better at catching esoteric problems.
> I am interested in testing an interaction between sex and income in
> predicting success on a dichotomous variable. If i model using oglm
> without the interaction and ", het(sex)" the lnsigma for sex is
> significant. When I include the sexXincome interaction with ",
> het(sex)" the lnsigma for sex is no longer significant (or even
> close). I interpret this to mean the interaction has in effect dealt
> with the hetero problem, correct?
Hopefully. As I note in my SMR piece (full citation is in the oglm 
help), sometimes you can have an interaction term or a hetero term, 
but not both at the same time. This might be because of collinearity 
between the terms. Overlap between vars in the choice and variance 
equations will be even more of a problem with a dichotomous dv. My 
inclination would be to declare victory at this point with the 
interaction model.
> But how can I tell if other predictors in the model that might also be
> problematic?
You probably just have to rely on what makes sense to you. There are 
always zillions of things that could be tossed into an equation, e.g. 
more variables, interaction terms, squared terms. You can't test 
everything but you can look at the more theoretically plausible things.

-------------------------------------------
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/