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From |
Navid Asgari <navid@nus.edu.sg> |

To |
"'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Very high t- statistics and very small standard errors |

Date |
Tue, 1 May 2012 09:45:25 +0800 |

No. I don't think you should be concerned. High significance level just shows how real the difference (or absence of it) between a random variable and its estimator is. Navid -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Laurie Molina Sent: Tuesday, May 01, 2012 9:18 AM To: statalist@hsphsun2.harvard.edu Subject: Re: st: Very high t- statistics and very small standard errors It is not the first time I hear people say that when you have a lot of observations everything is significant... Is it because the lenght of the confidence intervals is inversely related to the number of observations considered? Or could you tell me what is the logic behind saying that with a lot of observations everything is statistically significant? Thank you very much again! On Mon, Apr 30, 2012 at 9:10 PM, Richard Williams <richardwilliams.ndu@gmail.com> wrote: > At 07:54 PM 4/30/2012, Laurie Molina wrote: >> >> Hi everybody, >> I'm running some OLS with around 4 million observations and 6 >> explanatory variables. My coefficients are always significants, with >> very high t statistics and very low standard errors. for example t >> statistic=20.6 and standard error= .000023. This is a cross sectional >> data set. >> I have run the VIF test and for all the variables the variance >> inflation factor is less than 3. >> I have also ran the Durbin test creating an index variable (_n) to see >> wheter there is some sort of correlation in the error terms of my >> regresion, but there is not. >> Should I bee concerned about the significance of my coefficients? Is >> there any problem with getting such a large t statistics and small >> standard errors? >> Thank you all in advance and best regards!! > > > With 4 million cases it is hard not to get statistically significant > results. Whether they are worth caring about is another matter. For example, > a $2 difference in the incomes of men and women may be statistically > significant. $2 is not the same as $0. But how much you should care is > another matter. So, if everything is highly significant, I would ask myself > what the substantive significance of the findings is. (Actually I would do > that even if the results were not so significant - I think many people do > not pay enough attention to "So What?" sorts of questions.) > > > ------------------------------------------- > Richard Williams, Notre Dame Dept of Sociology > OFFICE: (574)631-6668, (574)631-6463 > HOME: (574)289-5227 > EMAIL: Richard.A.Williams.5@ND.Edu > WWW: http://www.nd.edu/~rwilliam > > > * > * 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/ * * 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: Very high t- statistics and very small standard errors***From:*Laurie Molina <molinalaurie@gmail.com>

**Re: st: Very high t- statistics and very small standard errors***From:*Richard Williams <richardwilliams.ndu@gmail.com>

**Re: st: Very high t- statistics and very small standard errors***From:*Laurie Molina <molinalaurie@gmail.com>

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