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 <[EMAIL PROTECTED]> 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: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] On Behalf Of Liaw, Andy > > Sent: Friday, May 25, 2007 12:04 PM > > To: [EMAIL PROTECTED]; Frank E Harrell Jr > > Cc: r-help > > Subject: Re: [R] normality tests [Broadcast] > > > > From: [EMAIL PROTECTED] > > > > > > On 25/05/07, Frank E Harrell Jr <[EMAIL PROTECTED]> wrote: > > > > [EMAIL PROTECTED] 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 > > > > > > ______________________________________________ > > > [email protected] 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}} > > > > ______________________________________________ > > [email protected] 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 > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
