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Re: st: comparing probit coefficients across two groups
From
Richard Williams <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: comparing probit coefficients across two groups
Date
Sun, 6 Jan 2013 14:01:45 -0500
In all modesty I agree with Bill. ;-) I think my slides are pretty
clear on how to proceed, but if not you can read the articles the
slides draw from. But just to be explicit,
* after controlling for hetero, you can test to see whether
interaction terms, e.g. Gender*whatever, are significant
* you can try to make the hetero problem go away by modifying the
model, e.g. In my example I showed how adding articles^2 made a hetero
equation unnecessary
* you can instead take Long's approach and just compare predicted
probabilities for the two groups,
* and, although not in my notes, Maarten's suggestion of looking at
odds ratios has been suggested by others.
So in short, a lot of information is already out there, and there is
code that shows how to do things in Stata (some of it is in my slides
and other code can be found in the articles that are mentioned). I
don't think there is much to be gained by retyping things that have
already been written up so I think the thing to do now is just look
over the materials already suggested more carefully.
Sent from my iPad
On Jan 6, 2013, at 12:22 PM, William Buchanan
<[email protected]> wrote:
> Hi Ebru,
>
> If you looked at the slide shows that Richard directed you towards it seems pretty clear and gives you working syntax that you could likely generalize to your specific research/variables.
>
> <from below>
>>> http://www3.nd.edu/~rwilliam/xsoc73994/L31.pdf
>>> http://www3.nd.edu/~rwilliam/xsoc73994/L31H.pdf
>
>
> HTH,
> Billy
>
>
> On Jan 6, 2013, at 9:08 AM, Ebru Ozturk wrote:
>
>> The thing is I still do not get how you compare coefficients across groups (i.e. female versus male). The papers generally explain how to compare across models not groups. For instance, how do we interpret the outcome of oglm estimation with heterogeneous choices? How do we compare male and female? Do we need to run two different models one with female and the other with male? Then compare the coefficients?
>>
>> oglm warm yr89 male white age ed prst, het(yr89 male)
>> oglm warm yr89 female white age ed prst, het(yr89 female)
>>
>> ----------------------------------------
>>> From: [email protected]
>>> Date: Fri, 4 Jan 2013 16:22:46 -0500
>>> Subject: Re: st: comparing probit coefficients across two groups
>>> To: [email protected]
>>>
>>> Well, yes. That is why I called it "Using heterogeneous choice models
>>> to compare logit and probit coefficients across groups." ;-) It builds
>>> on Allison's example and gives various others. But see my handout for
>>> other takes on the problems and possible solutions.
>>>
>>> Sent from my iPad
>>>
>>> On Jan 4, 2013, at 4:13 PM, Ebru Ozturk <[email protected]> wrote:
>>>
>>>> Allison's (1999) paper can answer the question of e.g. is the effect of education on income greater for men than it is for women?. But when I read the paper titled "Using Heterogeneous Choice Models To Compare Logit and Probit Coefficients Across Groups" (Williams, 2009) do you think it also focuses on comparison of coefficients across groups?
>>>>
>>>> ----------------------------------------
>>>>> Date: Fri, 4 Jan 2013 15:24:03 -0500
>>>>> To: [email protected]; [email protected]
>>>>> From: [email protected]
>>>>> Subject: Re: st: comparing probit coefficients across two groups
>>>>>
>>>>> At 01:25 PM 1/4/2013, Ebru Ozturk wrote:
>>>>>
>>>>>> Dear All,
>>>>>>
>>>>>> I run two models below with Probit estimation on Stata 10. First
>>>>>> model covers firms that collaborate and the second model covers
>>>>>> firms that do not collaborate. I want to compare the coefficients'
>>>>>> of "s_breadth" variable. I cannot understand quite that whether
>>>>>> -oglm- command applies to this type of problem. Can anyone make it clear?
>>>>>>
>>>>>>
>>>>>> ///// example //////
>>>>>>
>>>>>> probit radical_d businessgrp logemp continuous_rd process_inn
>>>>>> product_inn total_innv ind1 s_breadth if collab_developd==1
>>>>>> estimates store collab1
>>>>>> probit radical_d businessgrp logemp continuous_rd process_inn
>>>>>> product_inn total_innv ind1 s_breadth if collab_developd==0
>>>>>> estimates store collab0
>>>>>> suest collab1 collab0
>>>>>> test [collab1]s_breadth =
>>>>>> [collab0]s_breadth
>>>>>
>>>>> First off, given dichotomous DV and probit link, you might as well
>>>>> use -hetprob- as opposed to -oglm-.
>>>>>
>>>>> Second there are various issues involved in comparing coefficients
>>>>> across groups. Various solutions have been proposed. Personally I
>>>>> think the discussions of the problems may be stronger than the
>>>>> discussions of the solutions. For a summary, see
>>>>>
>>>>> http://www3.nd.edu/~rwilliam/xsoc73994/L31.pdf
>>>>>
>>>>> http://www3.nd.edu/~rwilliam/xsoc73994/L31H.pdf
>>>>>
>>>>> But, reading the articles listed at the end (starting with Allison's
>>>>> 1999 paper) will yield a clearer picture.
>>>>>
>>>>>
>>>>> -------------------------------------------
>>>>> 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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