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Re: st: statistical significance of cut points in ordered logit


From   Grace Jessie <gracejessie@hotmail.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   Re: st: statistical significance of cut points in ordered logit
Date   Mon, 17 May 2010 11:46:36 +0000

Statalists,
I got the material http://www.nd.edu/~rwilliam/xsoc63993/l91.pdf provided by Maarten, which is helpful. Thank you!
After typing the following in the Stata, I found some obersavtions were suprising to me(see table A). In table A, For example,xb[1] is obviously bigger than the coefficient of cut1,so the value for Y should equal 2. However, from the values for pr1 pr2 pr3, the value for pr1 is the biggest, which means the most likely outcome for Y is 1. Why not consistent?  The doubt with other observations in table A is the same. 
Additionally, what does the statistical significance of cut points in ordered logit mean, which has not been answered in the posting before? I found there are no z or P>|z| for cut points, though I could get it.
 
use http://www.nd.edu/~rwilliam/stats2/statafiles/shuttle2.dta, clear
ologit distress date temp, nolog
Ordered logistic regression                       Number of obs   =         23
                                                  LR chi2(2)      =      12.32
                                                  Prob> chi2     =     0.0021
Log likelihood =  -18.79706                       Pseudo R2       =     0.2468
------------------------------------------------------------------------------
    distress |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        date |    .003286   .0012662     2.60   0.009     .0008043    .0057677
        temp |  -.1733752   .0834473    -2.08   0.038     -.336929   -.0098215
-------------+----------------------------------------------------------------
       /cut1 |   16.42813   9.554813                      -2.29896    35.15522
       /cut2 |   18.12227   9.722293                     -.9330729    37.17761
------------------------------------------------------------------------------
predict xb,xb
predict pr1 pr2 pr3
 
table A
  +--------------------------------------------------------------------+
  | distress   date   temp         xb        pr1        pr2        pr3 |
  |--------------------------------------------------------------------|
  |     None   8732     70   16.55703   .4678189    .359285   .1728961 |
  |   1 or 2   9341     81   16.65107   .4444934   .3687458   .1867608 |
  |   3 plus   9434     75   17.99692   .1723883   .3589076    .468704 |
  |   1 or 2   9461     76   17.91227   .1848028   .3675054   .4476918 |
  +--------------------------------------------------------------------+
Hope for any help!

Regards,
Grace
 
  		 	   		  
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