Quite right, John! I have 2 additional questions:
1) Why test for normality of residuals? Suppose you reject -- then what? (residual plots may give information on skewness, multi-modality, data "anomalies" that can affect the data analysis). 2) Why test for normality? Is it EVER useful? Suppose you reject -- then what? (I am tempted to add a 3rd question -- why test at all? -- but that is perhaps too iconoclastic and certainly off topic. Let the hounds remain leashed for now.) Cheers, -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA "The business of the statistician is to catalyze the scientific learning process." - George E. P. Box > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of John Fox > Sent: Friday, October 15, 2004 5:43 AM > To: 'Federico Gherardini'; [EMAIL PROTECTED] > Subject: RE: [R] Testing for normality of residuals in a > regression model > > Dear Federico, > > A problem with applying a standard test of normality to LS > residuals is that > the residuals are correlated and heterskedastic even if the standard > assumptions of the model hold. In a large sample, this is > unlikely to be > problematic (unless there's an unusual data configuration), > but in a small > sample the effect could be nontrivial. > > One approach is to use BLUS residuals, which transform the LS > residuals to a > smaller set of uncorrelated, homoskedastic residuals (assuming the > correctness of the model). A search of R resources didn't > turn up anything > for BLUS, but they shouldn't be hard to compute. This is a > standard topic > covered in many econometrics texts. > > You might consider the alternative of generating a > bootstrapped confidence > envelope for the QQ plot; the qq.plot() function in the car > package will do > this for a linear model. > > I hope this helps, > John > > -------------------------------- > John Fox > Department of Sociology > McMaster University > Hamilton, Ontario > Canada L8S 4M4 > 905-525-9140x23604 > http://socserv.mcmaster.ca/jfox > -------------------------------- > > > -----Original Message----- > > From: [EMAIL PROTECTED] > > [mailto:[EMAIL PROTECTED] On Behalf Of > > Federico Gherardini > > Sent: Friday, October 15, 2004 7:44 AM > > To: [EMAIL PROTECTED] > > Subject: [R] Testing for normality of residuals in a > regression model > > > > Hi all, > > > > Is it possible to have a test value for assessing the > > normality of residuals from a linear regression model, > > instead of simply relying on qqplots? > > I've tried to use fitdistr to try and fit the residuals with > > a normal distribution, but fitdsitr only returns the > > parameters of the distribution and the standard errors, not > > the p-value. Am I missing something? > > > > Cheers, > > > > Federico > > > > ______________________________________________ > > [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 > > ______________________________________________ > [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 > ______________________________________________ [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