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From |
John Litfiba <cariboupad@gmx.fr> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: too good to be true : lr test in mlogit? |

Date |
Fri, 13 May 2011 10:45:37 +0200 |

Thank you so much for your kind and precise answer, Nick I would be definitively interested if by chance you have in mind a paper that discuss the large sample side effects on P-values that you mention Best Regards, On 13 May 2011 10:31, Nick Cox <njcoxstata@gmail.com> wrote: > I see nothing surprising here. The likelihood is the product of many > very small probabilities, so will be very small overall. The P-values > are at least in part a side-effect of using a very large sample size. > I don't know that a model with such a low pseudo-R-square is "too good > to be true", but it depends on your expectations. If this is analysis > of data on people, as I wildly guess, the Maarten Buis argument that > high levels of "explanation" are not to be expected given what else we > know about the many determinants and influences on human behaviour > could apply. > > Present-day significance testing machinery was largely designed in the > first few decades of the 20th century to safeguard natural scientists > against over-interpreting results from very small samples. Present-day > social scientists in the early 21st century need other measures to > safeguard themselves against over-interpreting significance tests from > very large samples. > > On Fri, May 13, 2011 at 9:12 AM, John Litfiba <cariboupad@gmx.fr> wrote: >> Dear all (again) >> >> I was wondering if my results seems too good to be true. I run a >> multinomial logit for yvar (caterical variable with 4 possible values) >> and I obtain the following results : >> >> 1) It is normal to obtain such a negative log likelihood when we use >> very large sample, right ? (n=2 millions here) >> 2) if the association (for example given by tabulation) show that >> there is strong association between yvar and xvar1 then it is >> plausible to obtain this fastastic LR statistic of... 140000 ?? >> >> >> Many many thanks in advance >> >> mlogit yvar xvar1 xvar2 >> >> Iteration 0: log likelihood = -1953742.5 >> Iteration 1: log likelihood = -1900152 >> Iteration 2: log likelihood = -1883338.4 >> Iteration 3: log likelihood = -1880317 >> Iteration 4: log likelihood = -1880312.7 >> Iteration 5: log likelihood = -1880312.7 >> >> Multinomial logistic regression Number of obs = 2227058 >> LR chi2(6) = 146859.43 >> Prob > chi2 = 0.0000 >> Log likelihood = -1880312.7 Pseudo R2 = 0.0376 >> >> ------------------------------------------------------------------------------ >> order | Coef. Std. Err. z P>|z| [95% Conf. Interval] >> -------------+---------------------------------------------------------------- >> yvar0 | (base outcome) >> -------------+---------------------------------------------------------------- >> yvar1 | >> xvar1 | -2.137044 .0104876 -203.77 0.000 -2.157599 -2.116489 >> xvar2| -.0099444 .0001223 -81.32 0.000 -.0101841 -.0097047 >> _cons | 1.708873 .0125759 135.88 0.000 1.684225 1.733522 >> -------------+---------------------------------------------------------------- >> yvar2 | >> xvar1 | .8905294 .0734511 12.12 0.000 .7465678 1.034491 >> xvar2 | -.0087927 .0003393 -25.92 0.000 -.0094576 -.0081277 >> _cons | -3.672227 .0758592 -48.41 0.000 -3.820908 -3.523546 >> -------------+---------------------------------------------------------------- >> yvar3 | >> xvar1 | -3.826486 .0113315 -337.69 0.000 -3.848695 -3.804276 >> xvar2 | -.0054125 .0002488 -21.76 0.000 -.0059002 -.0049249 >> _cons | 1.244583 .0180673 68.89 0.000 1.209171 1.279994 >> ------------------------------------------------------------------------------ >> * > > * > * 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/

**Follow-Ups**:**Re: st: too good to be true : lr test in mlogit?***From:*Maarten Buis <maartenlbuis@gmail.com>

**References**:**st: too good to be true : lr test in mlogit?***From:*John Litfiba <cariboupad@gmx.fr>

**Re: st: too good to be true : lr test in mlogit?***From:*Nick Cox <njcoxstata@gmail.com>

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