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RE: st: Brant's Test for Parallel Lines


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Brant's Test for Parallel Lines
Date   Fri, 14 Oct 2011 16:54:52 -0400

Yes, the test is of course more powerful at larger N, but that doesn't necessarily mean that the discrepancies it is detecting are trivial (ignorable), without more detailed diagnostics on precisely where the misfit is arising from (i.e., which covariate effects violate the assumption). Why not use a partial proportional odds model instead? 


Williams, R. (2006). Generalized ordered logit/partial proportional odds models for ordinal dependent variables. The Stata Journal, 6(1), 58–82.
http://www.stata-journal.com/abstracts/st0097.pdf 

http://ideas.repec.org/c/boc/bocode/s453401.html

 

Cam


> From: stephen.d.clark@ntlworld.com
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Brant's Test for Parallel Lines
> Date: Fri, 14 Oct 2011 21:36:00 +0100
> 
> Hello, 
> 
> I have an ordered logit model that uses a large amount of data, 2.5 million
> cases. Brant's test for parallel lines is significant (p>chi2 = 0.00) which
> suggest that the model I am using is inappropriate. However, I have found
> various references that suggest the test is pessimistic with very large
> samples - highlighting small differences that are not actually critical. I
> cannot get access to Brant original paper so I would welcome some advice as
> to whether this is likely to be the case here. Is there a better test
> available for large samples?
> 
> 
> 
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