# RE: st: St: Ordered Logit Question

 From "Jason Dean, Mr" To "statalist@hsphsun2.harvard.edu" Subject RE: st: St: Ordered Logit Question Date Fri, 8 May 2009 17:00:56 -0400

```Hmm, I'll have to take a look at it again. But when I run separate ologits and do predicted values they are much different then when I combine the sample and include a immigrant dummy (and of course interact all covariates). Maybe I made a typo in my code.

________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard Williams [Richard.A.Williams.5@ND.edu]
Sent: Friday, May 08, 2009 5:41 PM
To: statalist@hsphsun2.harvard.edu; statalist@hsphsun2.harvard.edu
Subject: RE: st: St: Ordered Logit Question

At 03:20 PM 5/8/2009, Jason Dean, Mr wrote:
>Hi, you can include interation terms for the explanitory variables
>but not for the cut point (ancillary) paramaters. I find these to be
>much different between groups.

Not true, actually.  Simply including a dummy var for group
membership in ologit allows for index shift, e.g. if the coefficient
for group was 1, you could interpret that as saying all the cut
points were 1 point higher for one of the groups.

gologit2 (available from SSC) also allows for cut-point shift, i.e.
the cut-points can differ by non-constant amounts.  Maybe the first
cut point is one point higher, the 2nd is only .5 points higher,
etc.  Do something like

gologit2 y x1 x2 x3 group, npl(group)

As discussed earlier, there is the question of whether these group
coefficients reflect real effects or reflect differences in
measurement, i.e. groups use different cut points when reporting
their responses on the ordinal variable.  Of course, both might be
going on,  but if so I don't know how you would disentangle the two.

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Richard Williams, Notre Dame Dept of Sociology
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EMAIL:  Richard.A.Williams.5@ND.Edu
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