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From |
Nick Cox <njcoxstata@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: RE: Mean test in a Likert Scale |

Date |
Mon, 3 Sep 2012 16:08:02 +0100 |

I don't prescribe or proscribe. If a predictor is ordinal, I'd guess that using indicator variables is most likely to be the best strategy. But I don't rule out, a priori or even prima facie or ex cathedra, that entering an ordinal variable "as is" might work well. Or even that there is a case for using both the predictor and a set of indicator variables. Similarly, how to treat something measured in US dollars is not something laid down in advance. It's most likely that I would want to transform it. I don't believe, by the way, that "anything goes" in data analysis, but on this point I think flexibility scores over dogmatism. Nick On Mon, Sep 3, 2012 at 3:54 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote: > Nick and Maarten, Note, that Kmenta's message is to prefer models with > less restrictions. > > Moreover, are you suggesting we can deal in the same manner with > quantitative values and ordinal variables? if our independent > variables are what subjects marked on a questionnaire on a scale > between 1 to 5 is the statistical treatment within a regression > analysis framework should be identical to an independent variable > measured in US dollars? > > On Mon, Sep 3, 2012 at 2:27 AM, Maarten Buis <maartenlbuis@gmail.com> wrote: >> On Mon, Sep 3, 2012 at 11:01 AM, Nick Cox wrote: >>> Econometricians' practice seems almost invariably looser than that -- >>> and a good thing too -- although the idea that an analysis is correct >>> or incorrect, and no shades of grey, still seems pervasive. >> >> What amuses me are the occasional reference to "correct models", which >> is just a contradiction in terms. A model is by definition a >> simplification of reality, and simplifying reality is really central >> to what a model is. If reality where so simple we could understand it >> without simplification we would not need a model. However, >> simplification is just another word for "wrong in some useful way". So >> a correct model either does not simplify and is thus not a model, or >> it is not as correct as the author thinks it is. >> >> -- Maarten >> >> --------------------------------- >> Maarten L. Buis >> WZB >> Reichpietschufer 50 >> 10785 Berlin >> Germany >> >> http://www.maartenbuis.nl >> --------------------------------- >> * >> * For searches and help try: >> * http://www.stata.com/help.cgi?search >> * http://www.stata.com/support/statalist/faq >> * http://www.ats.ucla.edu/stat/stata/ > > > > -- > Dr. Yuval Arbel > School of Business > Carmel Academic Center > 4 Shaar Palmer Street, > Haifa 33031, Israel > e-mail1: yuval.arbel@carmel.ac.il > e-mail2: yuval.arbel@gmail.com > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/statalist/faq > * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**Re: st: RE: Mean test in a Likert Scale***From:*Ulrich Kohler <kohler@wzb.eu>

**Re: st: RE: Mean test in a Likert Scale***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: RE: Mean test in a Likert Scale***From:*Ulrich Kohler <kohler@wzb.eu>

**Re: st: RE: Mean test in a Likert Scale***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: RE: Mean test in a Likert Scale***From:*Yuval Arbel <yuval.arbel@gmail.com>

**Re: st: RE: Mean test in a Likert Scale***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: RE: Mean test in a Likert Scale***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: RE: Mean test in a Likert Scale***From:*Yuval Arbel <yuval.arbel@gmail.com>

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