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Re: st: ordered logistic regression with endogenous variable

From   "Justina Fischer" <>
Subject   Re: st: ordered logistic regression with endogenous variable
Date   Thu, 11 Oct 2012 15:48:27 +0200

Dear Mr Verkuilen,

we both do not know what type of ordered variable Anat is using. 

As you might have noticed, we both give the same advise, for obviously the same reason(s).

Whether or not effect size is meaningful depends on the research question; I am sure your supervisor will agree with me on that statement.
In many of my publications on happiness (LFS), observing an effect or not was the most important question, whereas magnitude played only a minor role for the referees. 

Best regards

Justina Fischer, PhD
assoc. prof. 

-------- Original-Nachricht --------
> Datum: Thu, 11 Oct 2012 09:37:33 -0400
> Von: "JVerkuilen (Gmail)" <>
> An:
> Betreff: Re: st: ordered logistic regression with endogenous variable

> On Thu, Oct 11, 2012 at 8:30 AM, Justina Fischer <>
> wrote:
> > Hi Anat
> >
> > some practical advise:
> >
> > Ferrer-i-Carbonell, A. and Frijters, P. (2004), How Important is
> Methodology for the estimates of the determinants of Happiness?. The Economic
> Journal, 114: 641–659.
> >
> > have shown for 10-category life satisfaction data that the bias w.r.t.
> direction and significance from using OLS in place of an ordered probit
> estimation is negligeably small.
> My dissertation advisor and I were reviewers on that article as I
> recall, but we were not so favorable about their claims. I'm not so
> sure what you can determine about an estimator from analyzing one
> specific dataset as opposed to a careful consideration of the model.
> > Hence, I would suggest using ivreg2. Just do not try to discuss the size
> of the effect, but focus on direction and significance in your
> interpretation.
> I think you can probably get away with -ivreg2- assuming the DV isn't
> highly skewed or coarse. However, effect size is still meaningful, or
> as meaningful as it ever is for Likert-type scales. Switching to
> -oprobit- doesn't all of a sudden make it more legitimate to talk
> about the effects. For ordinal data -oprobit- has better statistical
> properties and the validity of a linear model is more likely to be
> true.
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