Re: st: Regression Across Two Groups

[Maarten Buis <maartenlbuis@gmail.com>]

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.

-- Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany


http://www.maartenbuis.nl
--------------------------
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