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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: test of significant between coefficients |

Date |
Tue, 27 Sep 2011 17:16:40 +0100 |

See also the thread starting here http://www.stata.com/statalist/archive/2010-12/msg00033.html Nick On Tue, Sep 27, 2011 at 4:35 PM, Nick Cox <njcoxstata@gmail.com> wrote: > Richard's answer overlaps with mine, which is fine. > > I want to underline the idea that often coefficients should be thought > as being bundled together. For example, if a cosine term is included > in a model a sine term should be too. Leaving out one or the other can > omit some useful information about phase even if one coefficient is > not significant. A more widely familiar example is a set of > indicators. Degrading them so that all are significant just coarsens a > model. > > Come to think of it, we've have had this discussion before. Just > search for "Richard Williams" in the Statalist archives. > > Nick > > On Tue, Sep 27, 2011 at 3:48 PM, Richard Williams > <richardwilliams.ndu@gmail.com> wrote: >> At 10:35 AM 9/27/2011, Andrea Rispoli wrote: >>> >>> Dear Statalisters, >>> I am running a test of significance between two coefficients of the >>> same OLS regression. >>> My question is : if the two coefficients are not significant, does it >>> still make sense to conduct the test? I am asking because sometimes >>> while the individual coefficients are not significant the difference >>> between them is significant, so I was trying to understand the meaning >>> of this result. >>> Thank you! >>> AR >> >> It can happen. The individual tests are testing whether the coefficients >> equal zero. The equality test might be testing whether, say, -.5 >> significantly differs from .5. In any event, there is nothing that says all >> your tests have to be logically consistent with each other. The overall F or >> chi-square statistic might be significant for a model, while none of the >> individual coefficients are. >> >> A more common situation might be where a coefficient is significant in one >> group but not in another. I always warn my students to be careful about >> saying X is important for one group but not the other. If, say, you are >> comparing whites and black, your white sample size might be much larger, >> which can help the effect to achieve significance for whites but not blacks. >> The actual estimated coefficients, however, may be quite similar. >> > * * 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: test of significant between coefficients***From:*Andrea Rispoli <andrea.rspl@gmail.com>

**Re: st: test of significant between coefficients***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: test of significant between coefficients***From:*Nick Cox <njcoxstata@gmail.com>

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