Re: [R] normality tests

From: <gatemaze_at_gmail.com>
Date: Fri, 25 May 2007 17:53:10 +0100

On 25/05/07, Frank E Harrell Jr <f.harrell_at_vanderbilt.edu> wrote:
> gatemaze@gmail.com wrote:
> > Hi all,
> >
> > apologies for seeking advice on a general stats question. I ve run
> > normality tests using 8 different methods:
> > - Lilliefors
> > - Shapiro-Wilk
> > - Robust Jarque Bera
> > - Jarque Bera
> > - Anderson-Darling
> > - Pearson chi-square
> > - Cramer-von Mises
> > - Shapiro-Francia
> >
> > All show that the null hypothesis that the data come from a normal

> > distro cannot be rejected. Great. However, I don't think it looks nice
> > to report the values of 8 different tests on a report. One note is
> > that my sample size is really tiny (less than 20 independent cases).

> > Without wanting to start a flame war, are there any advices of which
> > one/ones would be more appropriate and should be reported (along with
> > a Q-Q plot). Thank you.
> >
> > Regards,
> >
>
> Wow - I have so many concerns with that approach that it's hard to know
> where to begin. But first of all, why care about normality? Why not
> use distribution-free methods?
>
> You should examine the power of the tests for n=20. You'll probably
> find it's not good enough to reach a reliable conclusion.

And wouldn't it be even worse if I used non-parametric tests?

>
> Frank
>
>
> --
> Frank E Harrell Jr Professor and Chair School of Medicine
> Department of Biostatistics Vanderbilt University
>

-- 
yianni

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Received on Fri 25 May 2007 - 16:57:49 GMT

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