[Limdep Nlogit List] Interpretation of Random coefficients ordered logit parameters

Achilleas' gmail avassilopoulos.aua at gmail.com
Thu Feb 21 23:29:40 AEDT 2019


Dear Prof. Greene,
 
I agree about KDE but from its shape I (probably wrongly) expected that the
confidence interval of some coefficients would be away from zero.

The centipede plot is exactly what I need to show and actually it is the
reason I started this thread. The plot shows observations around the
horizontal axis and long lines (conf. intervals) that include zero in all
observations. My worry was that this picture was  not compatible with a
stat.significant estimate unconditional  standard deviation and might
indicate random noise. 

I understand this is not the case so I will stick to individual-specific
means and SD's to judge the effect of X1, X2.

Thank you for your detailed reply.

Best,
Achilleas

-----Original Message-----
From: Limdep <limdep-bounces at mailman.sydney.edu.au> On Behalf Of William
Greene via Limdep
Sent: Thursday, February 21, 2019 13:04
To: Limdep and Nlogit Mailing List <limdep at mailman.sydney.edu.au>
Cc: William Greene <wgreene at stern.nyu.edu>
Subject: Re: [Limdep Nlogit List] Interpretation of Random coefficients
ordered logit parameters

Achilleas.  Your KDE is plotting the variation of the means of the
conditional distributions across the individuals in the sample.  From what
you describe it sounds like you seek the range of variation of the within
individual distributions (that is, the conditional distributions).
There is a discussion of "centipede plots" in your manual that does this
sort of thing. You might search for that material and see if it does what
you are looking for.  It uses the individual specific means and conditional
standard deviations.
Regards,
Bill Greene

On Thu, Feb 21, 2019 at 1:12 AM Achilleas' gmail via Limdep <
limdep at mailman.sydney.edu.au> wrote:

> Dear Prof. Green,
>
> Thank you for your reply. Indeed my statement was confusing the way I 
> worded it. What I meant is that the conf. intervals of the conditional 
> estimates include zero and the lower (upper) bounds are strictly 
> negative (positive) for all individuals.
>
> So your last statement " Some of the distribution may be near zero 
> while more of the distribution may be quite far from zero " (which was 
> what I also
> expected) does not show itself in my data.
>
> When I plot the unconditional estimates with a kernel density plot, I 
> see that only a small part of the tail is below zero as expected.
>
> Could this be an indication of random noise that is captured by the 
> model as a distribution of population coefficients ?
>
> Best,
>
> Achilleas
>
> -----Original Message-----
> From: Limdep <limdep-bounces at mailman.sydney.edu.au> On Behalf Of 
> William Greene via Limdep
> Sent: Thursday, February 21, 2019 06:11
> To: Limdep and Nlogit Mailing List <limdep at mailman.sydney.edu.au>
> Cc: William Greene <wgreene at stern.nyu.edu>
> Subject: Re: [Limdep Nlogit List] Interpretation of Random 
> coefficients ordered logit parameters
>
> Achilleas:  Considering X1, your results suggest that the population 
> distribution of coefficients on X1 has a normal distribution with mean 
> of
> 0.12776 and a standard deviation of 0.62482.
> Interpretations of "statistical significance" in this context are 
> ambiguous.
> The statement
>
> However, when I look at the individual specific (conditional) 
> estimates, I find a strong indication of their effect being zero for all
(i.e.
> confidence
> intervals for all individuals are way far from zero on both ends)
>
> is contradictory.  It seems to state that the effects are close to 
> zero, but confidence intervals are far from zero.  What is true is 
> that the conditional estimates will vary around the mean of 0.12276.  
> The mean of the conditional estimates should equal the unconditional 
> estimate.
> The conditional standard deviations that are estimable will all be 
> less than the 0.62482, and the average of these conditional standard 
> deviations will also be strictly less than 0.62482.
> Characterizations of the distribution of random parameters should not 
> be based on "confidence intervals."  Some of the distribution may be 
> near zero while more of the distribution may be quite far from zero.
>
> /Bill Greene
>
>
>
> On Wed, Feb 20, 2019 at 2:07 PM Achilleas' gmail via Limdep < 
> limdep at mailman.sydney.edu.au> wrote:
>
> > Dear all,
> >
> >
> >
> > I'm estimating a Random Coefficients  Ordered Logit Model with Y an 
> > ordered variable and X1 and X2 independent dummy vars:
> >
> >
> >
> > SETPANEL; GROUP=ID; PDS=ROUNDS $
> >
> > ORDERED ; PANEL ; Lhs = Y
> >
> > ; Rhs = ONE, X1, X2
> >
> > ; MODEL= LOGIT $
> >
> > ORDERED  ; PANEL; Lhs = Y
> >
> > ; Rhs = one, X1, X2
> >
> > ; RPM
> >
> > ; par
> >
> > ; Fcn = one(n), X1(n), X2(n)
> >
> > ; HALTON
> >
> > ; MODEL= LOGIT $
> >
> >
> >
> > My results are as follows:
> >
> >
> >
> >         |Means for random parameters
> >
> > Constant|    8.33434***      .85987     9.69  .0000     6.64903
10.01966
> >
> >   X1    |     .12776         .32251      .40  .6920     -.50436
.75988
> >
> >   X2    |    -.03393         .33030     -.10  .9182     -.68131
.61344
> >
> >         |Scale parameters for dists. of random parameters
> >
> > Constant|    3.26244***      .22798    14.31  .0000     2.81560
3.70927
> >
> >   X1    |     .62482***      .21928     2.85  .0044      .19503
1.05460
> >
> >   X2    |     .78015***      .22758     3.43  .0006      .33409
1.22621
> >
> >
> >
> > My intuition is that for the X's, the results of the unconditional 
> > estimates mean that their effect is non-significant (i.e. zero) on 
> > aggregate but with strong individual variability (i.e. showing that 
> > for some individuals it is different from zero).
> >
> >
> >
> > However, when I look at the individual specific (conditional) 
> > estimates, I find a strong indication of their effect being zero for 
> > all
> (i.e.
> > confidence
> > intervals for all individuals are way far from zero on both ends)
> >
> >
> >
> > Is my interpretation mistaken?  And if not, how I can possibly 
> > explain the different conclusions I get from conditional vs 
> > unconditional
> estimates?
> >
> >
> >
> > Thank you,
> >
> >
> >
> > Achilleas
> >
> >
> >
> > _______________________________________________
> > Limdep site list
> > Limdep at mailman.sydney.edu.au
> > http://limdep.itls.usyd.edu.au
> >
> >
>
> --
> William Greene
> Department of Economics
> Stern School of Business, New York University
> 44 West 4 St., 7-90
> New York, NY, 10012
> URL: https://protect-au.mimecast.com/s/7NxuCr8DLRtRPgWOC7Ft1j?domain=people.stern.nyu.edu
> Email: wgreene at stern.nyu.edu
> Ph. +1.212.998.0876
> Editor in Chief: Journal of Productivity Analysis Editor in Chief:
> Foundations and Trends in Econometrics Associate Editor: Economics 
> Letters Associate Editor: Journal of Business and Economic Statistics 
> Associate
> Editor: Journal of Choice Modeling
> _______________________________________________
> Limdep site list
> Limdep at mailman.sydney.edu.au
> http://limdep.itls.usyd.edu.au
>
>
> _______________________________________________
> Limdep site list
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> http://limdep.itls.usyd.edu.au
>
>

--
William Greene
Department of Economics
Stern School of Business, New York University
44 West 4 St., 7-90
New York, NY, 10012
URL: https://protect-au.mimecast.com/s/7NxuCr8DLRtRPgWOC7Ft1j?domain=people.stern.nyu.edu
Email: wgreene at stern.nyu.edu
Ph. +1.212.998.0876
Editor in Chief: Journal of Productivity Analysis Editor in Chief:
Foundations and Trends in Econometrics Associate Editor: Economics Letters
Associate Editor: Journal of Business and Economic Statistics Associate
Editor: Journal of Choice Modeling
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