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From |
"Airey, David C" <david.airey@vanderbilt.edu> |

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

Subject |
Re: st: Statistical tests under heteroskedasticity |

Date |
Tue, 15 May 2012 23:01:31 -0500 |

. The abstract seems a bit strong for the content! Still, in a linear regression model if not a logistic regression model, vce(robust) is a useful option for a well specified model where the variances are not assumed to be constant. -Dave > Indeed, that is exactly the argument presented in: > Freedman, D.A. (2006). On the So-Called “Huber Sandwich Estimator” and “Robust Standard Errors”. The American Statistician, 60(4), 299-302. > http://www.stat.berkeley.edu/~census/mlesan.pdf > > > Cam > > From: david.airey@vanderbilt.edu > > To: statalist@hsphsun2.harvard.edu > > Date: Tue, 15 May 2012 10:09:49 -0500 > > Subject: Re: st: Statistical tests under heteroskedasticity > > > > . > > > > I think it is important (for people like me) to remember to tack on to the end of this correct statement: > > > > (1) provided the model for the expectations (means, for linear regression) is approximately correct, and > > (2) provided the sample size is large enough > > > > The vce(robust) option is not going to help a poor model, or a model missing important covariates. > > > > If desired, Stata provides more conservative robust options (vce(hc3)) for linear regression with smaller samples. > > > > > <> > > > On May 15, 2012, at 2:33 AM, Lukas wrote: > > > > > > > I use Stata 11.2 and I want to run several statistical tests to analyse my regression results. In my regression, I use the -robust- option but now I became aware, that heteroskedasticity invalidates my statistical tests such as hypothesis tests as well. > > > > > > > > Is there a way to run the -ttest- and -testparm- commands under heteroskedasticity without invalidating their results? > > > > > > Calculating robust standard errors -- or more properly, a robust VCE -- 'robustifies' all computations done with that VCE, including t-tests and F-tests. So if the only departure from i.i.d. errors is heteroskedasticity, the 'robust' option makes all subsequent test, testparm, lincom, etc. valid. > > > > > > Kit * * 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/

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