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Re: st: Ologit question


From   "Anat (Manes) Tchetchik" <anatmanes@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Ologit question
Date   Wed, 31 Oct 2012 15:58:47 +0200

Thank you Maaraten,
Running -test- yeilds :
 test

 ( 1)  [tier_reversed]profit = 0
 ( 2)  [tier_reversed]oncology = 0
 ( 3)  [tier_reversed]cardiology = 0
 ( 4)  [tier_reversed]clinical_services = 0
 ( 5)  [tier_reversed]length_stay_tot = 0
 ( 6)  [tier_reversed]age = 0
 ( 7)  [tier_reversed]income = 0
 ( 8)  [tier_reversed]H_index = 0
 ( 9)  [tier_reversed]publications = 0
 (10)  [tier_reversed]doctors = 0
 (11)  [tier_reversed]revenue = 0
       Constraint 11 dropped

           chi2( 10) =   24.65
         Prob > chi2 =    0.0060
not sure I understand what it means and how it referes to the cuts
Anat




On Wed, Oct 31, 2012 at 3:46 PM, Maarten Buis <maartenlbuis@gmail.com> wrote:
> On Wed, Oct 31, 2012 at 2:23 PM, Anat (Manes) Tchetchik wrote:
>> I ran an Ologit and received the following cutoffs:
>>
>>                 Coef.         Std. Err.           [ 95% Conf. Interval]
>>  /cut1 |  -1.798009   2.900799             -7.483471    3.887453
>>  /cut2 |   .7973023   2.793147             -4.677166    6.271771
>>  /cut3 |   2.902347   2.794626              -2.57502    8.379713
>> which means that the cutoffs are not significantly different.
>
> You seem to perform this test by looking at whether the confidence
> intervals overlap. This is not a correct way to perform such a test,
> as that way you ignore the covariances in the sampling distribution of
> these estimates. Instead you should use -test- if you want to perform
> such a test.
>
>> Does it mean that the entire model is worthless?
>
> No, statistical tests do not represent a relevant tradeoff you need to
> make when choosing a model. The tradeoff implicit in a statistical
> test is all about the probability of rejecting a true null hypothesis
> and the probability of not rejecting a false hypothesis. However, it
> is by definition impossible for a model to be "true". A model is by
> definition a simplification of reality, and a simplification is just
> another word for "wrong in some useful way". So you want your model to
> be wrong (simplify) in such a way that the results become manageable
> for a human brain to process, but at the same time you don't want your
> model to be too wrong so that it deviates too much from your raw
> observations. So selecting a model and doing a statistical test are
> fundamentally different beasts working with very different logics,
> which means that a statistical test just cannot inform you about which
> model is "right" or "wrong".
>
> -- Maarten
>
> ---------------------------------
> Maarten L. Buis
> WZB
> Reichpietschufer 50
> 10785 Berlin
> Germany
>
> http://www.maartenbuis.nl
> ---------------------------------
> *
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--
Anat Tchetchik, PhD
Department of Hotel and Tourism Management
Guilford Glazer Faculty of Business and Management
Ben-Gurion University of the Negev
P.O.Box: 653
Beer-Sheva, Israel, 84105

E-mail:       anat@som.bgu.ac.il
Phone         972-(0)8-6479735
Fax:           972-(0)8-6472920
Web:          http://cmsprod.bgu.ac.il/Eng/som/hotelmanage/Staff/Academic/ChechikA.htm
*
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