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Re: st: Regression Across Two Groups


From   Muhammad Anees <anees@aneconomist.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Regression Across Two Groups
Date   Wed, 14 Dec 2011 15:16:37 +0500

There are actually two variables describing earnings, one as a
dichomous (recorded in Yes or No) and and other as groups or interval.
The objective is to assess if such earnings from secondardy jobs also
depend on foreign qualification and if yes, then what is difference
between the regressions across the two groups based on foreign
qualification or no qualification.

On Wed, Dec 14, 2011 at 3:03 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> Thanks for the example.
>
> I see earnings as a coarsely categorised variable, fit for -intreg- or
> -ologit-. In what sense is earnings dichotomous (means, has two
> categories)? Why did you say you were interested in logit models?
>
> Nick
>
> On Wed, Dec 14, 2011 at 9:48 AM, Muhammad Anees <anees@aneconomist.com> wrote:
>> Thanks Nick for your suggestion.
>>
>> Sure, the data looks like which contains two different sample but
>> related. Foreign qualified and no foreign qualification are two
>> different dataset earch with the following sample data, only a sample,
>> actually the data consist two different samples in two different
>> files, which I can deal how to combine in stata for my purpose.
>>
>>
>>
>> ear     exper   gender  subject area    language
>> 0-5000  20      m       IT      rural   Urdu
>> 5000-10000      22      m       ENGINEER        urban   English
>> 10001-15000     15      f       ECONOMICS       rural   Urdu
>> 5000-10000      10      m       HR      urban   Urdu
>> 5000-10000      5       f       STRT MGT        urban   English
>> 10001-15000     8       f       MARK    urbna   English
>> 0-5000  9       m       SOCIOLOGY       rural   Urdu
>> 0-5000  17      m       IT      urban   Urdu
>>
>>
>> On Wed, Dec 14, 2011 at 2:39 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>> It's categorical/dichotomous, yet the example is [pro]portion of
>>> earnings from outside main job. Sounds like a fractional response from
>>> the latter. Muhammad: Give us an example of what observations look
>>> like before this gets any more obscure, please!
>>>
>>> On Wed, Dec 14, 2011 at 9:18 AM, Maarten Buis <maartenlbuis@gmail.com> wrote:
>>>> On Wed, Dec 14, 2011 at 6:25 AM, Muhammad Anees wrote:
>>>>> Sorry for not clarifying the story about the types of variables, like
>>>>> earnings which I have at hand as a categorical/dichotomous variable.
>>>>> For example if an individual has a portion of earnings from doing
>>>>> consultancies or involved in any R&D organizations beside their normal
>>>>> routine jobs. In this case, I was interested in comparing the
>>>>> regression models (across foreign qualified and not foreign qualified)
>>>>> of earnings on other predictors say experience, research training, job
>>>>> nature, industry, region (rural and urban) using logit/probit in case
>>>>> of categorical variables and similarly using OLS for continuous
>>>>> dependent variable which at least I do not have at this stage.
>>>>
>>>> This is still not clear. The independent/explanatory/right-hand-side/x
>>>> variables aren't relevant here, they can be of any type, it is the
>>>> type of  the dependent/explained/left-hand-side/y variable that
>>>> matters. Earnings is typically collected as either a continuous
>>>> variable (how much do you earn?) or as a choice from a set of
>>>> intervals (did you earn less than x$, between x$ and y$, etc.?). None
>>>> of these are correctly modeled as a logit/probit. In the former case I
>>>> would use a -glm- with the -link(log)- option, in the latter case I
>>>> would start with assigning each category with a reasonable
>>>> representative number and than use -glm- with the -link(log)- option.
>>>> There are other solutions for the latter problem, e.g. -intreg-, but
>>>> if the underlying distribution is non-normal, which is likely to be
>>>> the case with earnings, then it is unclear whether these alternatives
>>>> are any better. The comparison is than just a matter of adding the
>>>> appropriate dummies and/or interactions.
>>>
>>> *
>>> *   For searches and help try:
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>>> *   http://www.ats.ucla.edu/stat/stata/
>>
>>
>>
>> --
>>
>> Regards
>> ---------------------------
>> Muhammad Anees
>> Assistant Professor
>> COMSATS Institute of Information Technology
>> Attock 43600, Pakistan
>> www.aneconomist.com
>>
>> *
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>> *   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
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> *   http://www.ats.ucla.edu/stat/stata/



-- 

Regards
---------------------------
Muhammad Anees
Assistant Professor
COMSATS Institute of Information Technology
Attock 43600, Pakistan
www.aneconomist.com

*
*   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/


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