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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: goodness of fit measure fir ivtobit |

Date |
Mon, 24 Sep 2012 17:51:59 +0100 |

I am puzzled that you want to recommend what could easily be construed as evasion. Such comments are easy to handle. The conduct of debate is not constant across disciplines, or even places, but in many forums _not_ giving an R-squared would be suspicious too. Nick On Mon, Sep 24, 2012 at 5:43 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote: > Nick, if we are aware of the many limitations of the R-Squares that's > O.K. to report it. My fear is that during a presentation somebody will > see the low R-Squared and say that given that 88 percent of the > variance cannot be explained Anat's work is worthless, where this is > obviously not the case (and believe me, these things happened before). > > Finally, a nice anecdote from Johnston and Dinardo's textbook > (Econometric Methods fourth edition (1997) page 10): they quote > Plosser and Schwert, who found a +0.91 correlation between the log of > U.S. nominal income and the log of accumulated sunspots!!! > > On Mon, Sep 24, 2012 at 6:26 PM, Nick Cox <njcoxstata@gmail.com> wrote: >> That is a puzzling argument, if indeed it's an argument at all. >> >> I don't think anything much in statistics ensures a _causal_ >> relationship (presumably what Yuval means here), short of independent >> evidence on mechanism or process. >> >> If a model is not that great, readers need to know. Sometimes a low >> R-squared makes that vivid. >> >> (People who want to remind me how limited R-squared is should please >> note that I wrote the FAQ cited below, which comes decorated with >> multiple warnings.) >> >> Nick >> >> On Mon, Sep 24, 2012 at 5:12 PM, Yuval Arbel <yuval.arbel@gmail.com> wrote: >>> Anat, note that the possibility to calculate the log likelihood is >>> there regardless of the method of estimation you are employing. >>> >>> In addition, I would personally rather avoid presenting an R-Squared >>> of 0.12, particularly in these kinds of models. As is well known, high >>> R-Squared does not ensure casual relationship and low R-Squared does >>> not ensure lack of casual relationship >>> >>> On Mon, Sep 24, 2012 at 4:54 PM, Anat (Manes) Tchetchik >>> <anatmanes@gmail.com> wrote: >>>> I haven't thought about the count model, I will definitely try to run >>>> it! thanks much! >>>> >>>> On Mon, Sep 24, 2012 at 5:38 PM, Maarten Buis <maartenlbuis@gmail.com> wrote: >>>>> That does not sound like censoring at all. I would think of this as a >>>>> regular count model. There are examples on how to deal with such an >>>>> iv-model in -help gmm-. >>>>> >>>>> Hope this helps, >>>>> Maarten >>>>> >>>>> On Mon, Sep 24, 2012 at 4:11 PM, Anat (Manes) Tchetchik >>>>> <anatmanes@gmail.com> wrote: >>>>>> Austin Hi, >>>>>> Thank you very much for your reply! >>>>>> What I have as a dependent var. are 500 respondents' reports of the >>>>>> number of times they travelled abroad to visit their friends and >>>>>> relatives over the course of their adult lives. Some respondents yet, >>>>>> who have relatives abroad, did not travel at all. >>>>>> So the observations are censored at zero, with mean =2.2, max =50 and >>>>>> stdev= 3.8. >>>>>> Do you think in that case that the general methods of moments will be better? >>>>>> Thanks much!!! >>>>>> Anat >>>>>> >>>>>> On Sun, Sep 23, 2012 at 5:49 AM, Austin Nichols <austinnichols@gmail.com> wrote: >>>>>>> >>>>>>> Anat (Manes) Tchetchik <anatmanes@gmail.com>: >>>>>>> You can always -predict- and compute the squared correlation of >>>>>>> predictions with observed values: >>>>>>> http://www.stata.com/support/faqs/statistics/r-squared/ >>>>>>> but are you sure your -ivtobit- model is justified? What is the >>>>>>> process that results in observations being censored? I suspect you >>>>>>> have a lower limit at zero which is actually a very low conditional >>>>>>> mean rounded down to zero--am I right? You may be better off with a >>>>>>> -gmm- model. >>>>>>> >>>>>>> On Sat, Sep 22, 2012 at 5:33 PM, Anat (Manes) Tchetchik >>>>>>> <anatmanes@gmail.com> wrote: >>>>>>> > Dear statalisters, >>>>>>> > >>>>>>> > I wonder if anyone knows any goodness of fit that is appropriate for >>>>>>> > tobit with endogenous >>>>>>> > variables (ivtobit). Not as in "regular" tobit, stata does not report any >>>>>>> > goodness of fit measure, any idea how to estimate such a measure? >>>>>>> > Any response will be greatly appreciated.. >> * >> * 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**:**st: goodness of fit measure fir ivtobit***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*Austin Nichols <austinnichols@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*Maarten Buis <maartenlbuis@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*"Anat (Manes) Tchetchik" <anatmanes@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*Yuval Arbel <yuval.arbel@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*Nick Cox <njcoxstata@gmail.com>

**Re: st: goodness of fit measure fir ivtobit***From:*Yuval Arbel <yuval.arbel@gmail.com>

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