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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Regression Across Two Groups |

Date |
Wed, 14 Dec 2011 10:03:42 +0000 |

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: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * 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/ * * 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/

**Follow-Ups**:**Re: st: Regression Across Two Groups***From:*Muhammad Anees <anees@aneconomist.com>

**References**:**st: Regression Across Two Groups***From:*Muhammad Anees <anees@aneconomist.com>

**RE: st: Regression Across Two Groups***From:*Cameron McIntosh <cnm100@hotmail.com>

**Re: st: Regression Across Two Groups***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: Regression Across Two Groups***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: Regression Across Two Groups***From:*Muhammad Anees <anees@aneconomist.com>

**Re: st: Regression Across Two Groups***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: Regression Across Two Groups***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: Regression Across Two Groups***From:*Muhammad Anees <anees@aneconomist.com>

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