From: <gatemaze_at_gmail.com>

Date: Fri, 25 May 2007 19:23:03 +0100

Date: Fri, 25 May 2007 19:23:03 +0100

Thank you all for your replies.... they have been more useful... well in my case I have chosen to do some parametric tests (more precisely correlation and linear regressions among some variables)... so it would be nice if I had an extra bit of support on my decisions... If I understood well from all your replies... I shouldn't pay soooo much attntion on the normality tests, so it wouldn't matter which one/ones I use to report... but rather focus on issues such as the power of the test...

On 25/05/07, Lucke, Joseph F <Joseph.F.Lucke_at_uth.tmc.edu> wrote:

> Most standard tests, such as t-tests and ANOVA, are fairly resistant to

*> non-normalilty for significance testing. It's the sample means that have
**> to be normal, not the data. The CLT kicks in fairly quickly. Testing
**> for normality prior to choosing a test statistic is generally not a good
**> idea.
**>
**> -----Original Message-----
**> From: r-help-bounces_at_stat.math.ethz.ch
**> [mailto:r-help-bounces_at_stat.math.ethz.ch] On Behalf Of Liaw, Andy
**> Sent: Friday, May 25, 2007 12:04 PM
**> To: gatemaze_at_gmail.com; Frank E Harrell Jr
**> Cc: r-help
**> Subject: Re: [R] normality tests [Broadcast]
**>
**> From: gatemaze_at_gmail.com
**> >
**> > On 25/05/07, Frank E Harrell Jr <f.harrell_at_vanderbilt.edu> wrote:
**> > > gatemaze_at_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?
**>
**> I believe what Frank meant was that it's probably better to use a
**> distribution-free procedure to do the real test of interest (if there is
**> one) instead of testing for normality, and then use a test that assumes
**> normality.
**>
**> I guess the question is, what exactly do you want to do with the outcome
**> of the normality tests? If those are going to be used as basis for
**> deciding which test(s) to do next, then I concur with Frank's
**> reservation.
**>
**> Generally speaking, I do not find goodness-of-fit for distributions very
**> useful, mostly for the reason that failure to reject the null is no
**> evidence in favor of the null. It's difficult for me to imagine why
**> "there's insufficient evidence to show that the data did not come from a
**> normal distribution" would be interesting.
**>
**> Andy
**>
**>
**> > >
**> > > Frank
**> > >
**> > >
**> > > --
**> > > Frank E Harrell Jr Professor and Chair School
**> > of Medicine
**> > > Department of Biostatistics
**> > Vanderbilt University
**> > >
**> >
**> >
**> > --
**> > yianni
**> >
**> > ______________________________________________
**> > R-help_at_stat.math.ethz.ch mailing list
**> > https://stat.ethz.ch/mailman/listinfo/r-help
**> > PLEASE do read the posting guide
**> > http://www.R-project.org/posting-guide.html
**> > and provide commented, minimal, self-contained, reproducible code.
**> >
**> >
**> >
**>
**>
**> ------------------------------------------------------------------------
**> ------
**> Notice: This e-mail message, together with any
**> attachments,...{{dropped}}
**>
**> ______________________________________________
**> R-help_at_stat.math.ethz.ch mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide
**> http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
**>
*

-- yianni ______________________________________________ R-help_at_stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.Received on Fri 25 May 2007 - 18:43:15 GMT

Archive maintained by Robert King, hosted by
the discipline of
statistics at the
University of Newcastle,
Australia.

Archive generated by hypermail 2.2.0, at Fri 25 May 2007 - 22:31:06 GMT.

*
Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help.
Please read the posting
guide before posting to the list.
*