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Re: st: oglm and heterogeneous choice models


From   "Rourke O'Brien" <[email protected]>
To   [email protected]
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 <[email protected]> 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 <[email protected]> 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:  [email protected]
>> WWW:    http://www.nd.edu/~rwilliam
>>
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