From: <Cody_Hamilton_at_edwards.com>

Date: Fri, 25 May 2007 15:28:26 -0700

Date: Fri, 25 May 2007 15:28:26 -0700

Cody Hamilton, PhD

Edwards Lifesciences

Frank E Harrell Jr <f.harrell_at_vander To bilt.edu> "Lucke, Joseph F" Sent by: <Joseph.F.Lucke_at_uth.tmc.edu> r-help-bounces_at_st cc at.math.ethz.ch r-help <r-help_at_stat.math.ethz.ch> Subject Re: [R] normality tests 05/25/2007 02:42 [Broadcast] PM

Lucke, Joseph F 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.
*

Note that the CLT helps with type I error but not so much with type II error.

*>
*

> -----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.
**>>
**>>
**>>
**>
**>
**> ------------------------------------------------------------------------
**> ------
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**>
**> ______________________________________________
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**> PLEASE do read the posting guide
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**> and provide commented, minimal, self-contained, reproducible code.
**>
*

-- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University ______________________________________________ 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. ______________________________________________ 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 - 22:34:40 GMT

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