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

[Grace Jessie <gracejessie@hotmail.com>]

Tirthankar and Martin,
thank you for reply and help.
Sorry for my mistake. Yes, the material is provided by Richard  Williams and pointed out by Maarten.
Tirthankar, thank you for pointing out the problem and explanations. 
 
Regards,
Grace

----------------------------------------
> Date: Mon, 17 May 2010 17:40:40 +0530
> Subject: Re: st: statistical significance of cut points in ordered logit
> From: tirthankar.chakravarty@gmail.com
> To: statalist@hsphsun2.harvard.edu
>
> Grace,
>
> That is not how it works. There is an error term involved in these
> probability calculations as well. Specifically, for the observation
> where xb=16.55703,
> Pr(y=1|x) = Pr(xb+u <= cut1) = Pr(u <= -.1289)
> which, together with the assumed logistic distribution for the "u"s
> implies Pr(y=1|x) = invlogit(-.1289) = .46781954. Similarly,
> Pr(y=2|x) = Pr(cut1 <= xb+u <= cut2) = Pr(-.1289 <= u <= 1.56567) =
> invlogit(1.56567)-invlogit(-.1289) = .35934591
> and so on. If you were to write off the error term i.e., base
> inference on the expected probabilities (xb), you'd have certainties
> and not probabilities.
>
> T
>
> 2010/5/17 Martin Weiss :
>>
>> <>
>>
>> " I got the material http://www.nd.edu/~rwilliam/xsoc63993/l91.pdf provided
>> by Maarten, which is helpful."
>>
>>
>>
>> Just to be sure, the material you are referring to is provided by Richard
>> Williams, Maarten probably pointed you to it.
>>
>> HTH
>> Martin
>>
>>
>> -----Ursprüngliche Nachricht-----
>> Von: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Grace Jessie
>> Gesendet: Montag, 17. Mai 2010 13:47
>> An: statalist@hsphsun2.harvard.edu
>> Betreff: Re: st: statistical significance of cut points in ordered logit
>>
>>
>> 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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>
>
>
> --
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> recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
> belongs to Flg(κ) (where v is the free variable of r).
>
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