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Re: st: Statistical tests under heteroskedasticity


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   Mon, 14 May 2012 15:47:44 -0500

.

Thanks. I should have said approximately normal distributions of the parameter estimates.

-Dave


> Dave,
> 
> What's the part about normally distributed coefficients?  In the usual
> linear regression models, the coefficients are assumed to be
> constants.
> 
> If the departure from constant variance (of the errors) is systematic,
> it may point to a need for a transformation of the dependent variable.
> 
> David Hoaglin
> 
> On Mon, May 14, 2012 at 10:34 AM, Airey, David C
> <david.airey@vanderbilt.edu> wrote:
> > .
> >
> > I was just reviewing assumptions for linear regression (simple error structure).
> >
> > independence -- needed for all types of inference
> > normally distributed coefficients -- needed for all types of inference
> > constant variance -- needed for all types of inference; can be relaxed by robust standard errors
> > correct mean model -- needed for group comparison and prediction
> > normal residuals -- needed for prediction; not fixed by robust standard errors


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