[R] normality tests [Broadcast]
wssecn
wssecn at uol.com.br
Fri May 25 23:59:25 CEST 2007
The normality of the residuals is important in the inference procedures for the classical linear regression model, and normality is very important in correlation analysis (second moment)...
Washington S. Silva
> 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...
>
> Thanks again.
>
> 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.
>
More information about the R-help
mailing list