Re: st: compare regression coefficients between 2 groups (SUEST) across time and across subgroups in a data set

[Richard Williams <richardwilliams.ndu@gmail.com>]

At 10:55 AM 8/2/2011, Roland Teitzer wrote:
> We would like to find out wheather the regression coefficients we get from
> the "logit" command (binary logistic regression) differ significantly from
> each other.

This is a far more difficult problem than people realize. Paul 
Allison described the problem well in this piece:

Allison, Paul. 1999. "Comparing Logit and Probit Coefficients Across 
Groups." Sociological Methods and Research 28(2): 186-208.

However, I (and others) had problems with Allison's proposed 
solution. I discussed these issues & offer solutions in

http://www.nd.edu/~rwilliam/oglm/RW_Hetero_Choice.pdf

http://www.nd.edu/~rwilliam/oglm/oglm_Stata.pdf

Quoting from the abstract to my first paper,

Allison (1999) notes that comparisons of logit and probit 
coefficients across groups can be invalid and misleading. He proposes 
a procedure by which these problems can be corrected, and argues that 
"routine use [of this method] seems advisable" and that "it is hard 
to see how [the method] can be improved." We argue that, as 
originally proposed, this method can have serious problems and should 
not be applied on a routine basis. However, we also show that the 
model used by Allison is part of a larger class of models variously 
known as heterogeneous choice or location-scale models. We illustrate 
that there are several advantages to turning to this broader and more 
flexible class of models. Dependent variables can be ordinal in 
addition to binary, sources of heterogeneity can be better modeled 
and controlled for, and insights can be gained into the effects of 
group characteristics on outcomes that would be missed by other methods.

However, not everyone is crazy about my proposed solutions. For Scott 
Long's take, see

http://www.indiana.edu/~jslsoc/research_groupdif.htm

Maarten Buis has also made a case for using odds ratios when 
interpreting interactions:

http://www.maartenbuis.nl/publications/interactions.html

There seems to be a lot of work on this lately. I think the 
description of the problem is more clear-cut than the solutions are. 
I'm coming to the conclusion that the best thing to do is to make 
sure you only have continuous dependent variables...

> therefor we used the suest command but we are not quite sure if we used it
> correctly, as in the stata help the command is only described for linear
> regressions.
>
> we have two different kinds of logit model we want to compare.
>
> 1.)in the first case we have two independent subgroups of persons in a
> dataset (persons with german nationality and foreigners).
>
> we tried out this command ("poor" is the dependent, the others are the
> independant variables):
>
> logit poor women young old if german==1, or
>
> estimates store german
>
> logit poor women young old if turkish==1, or
>
> estimates store turkish
>
> suest german turkish
> test [german_poor]women= [turkish_poor]women
> test [german_poor]young= [turkish_poor]young
> test [german_poor]old= [turkish_poor]old
>
> 2.)in the second case we have date were there are mostly cross-sectional
> data, but also some panel-data (EU SILC-data)
>
> therefore we used this command:
>
> logit poor women young old if 2004==1, or
>
> estimates store data2004
>
> logit poor women young old if 2009==1, or
>
> estimates store data2009
>
> suest data2004 data2009
>
> test woman
> test young
> test old
>
> --> we looked up some helps for this problem, but they are written so
> complicated that we were even more confused afterwards.
> we would need a clear syntax.
>
> Could somebody tell us which syntax we schould use for which problem?
>
> Thank you and sorry for asking such "simple" questions...
>
>
>
>
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-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME:   (574)289-5227
EMAIL:  Richard.A.Williams.5@ND.Edu
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