Re: st: Nominal or ordinal?

[Maarten buis <maartenbuis@yahoo.co.uk>]

--- On Fri, 13/8/10, Richard Williams wrote:
> use "http://www.indiana.edu/~jslsoc/stata/spex_data/ordwarm2.dta";,
> clear
> tab1 warm
> reg warm  yr89 male white age ed prst
> ologit warm  yr89 male white age ed prst, nolog
> 
> In this example, the T/Z values are virtually identical
> across the two methods, and the coefficients are in the same
> ratios to each other (i.e. in the ologit the coefficients
> are all about twice as large as they are in the
> regression).
> 
> Of course, this is just one example, and there are other
> ordinal variables where it is clearly unreasonable to think
> that the categories are evenly spaced. But this gives hope
> that nothing too terrible happens if your typical scale
> ranging from "Strongly Disagree" to "Strongly Agree" is
> analyzed by ols rather than ordinal regression.

The idea of distances between categories is quite natural in
stereotype logistic regression (-slogit-), here the phi s
can be thought of as a scale for your dependent variable. If
you apply that idea to your example you can see that the 
hypothesis of equal distances between the categories cannot
be rejected.

*------------------- begin example ------------------
use "http://www.indiana.edu/~jslsoc/stata/spex_data/ordwarm2.dta";, clear
tab1 warm
constraint 1 [phi1_2]_cons = 2/3
constraint 2 [phi1_3]_cons = 1/3
slogit warm  yr89 male white age ed prst
est store a
slogit warm  yr89 male white age ed prst, constraint(1 2)
est store b 
lrtest a b
*----------------- end example ------------------------
(For more on examples I sent to the Statalist see: 
http://www.maartenbuis.nl/example_faq )

Hope this helps,
Maarten

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

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


      

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