On Wed, 28 Oct 2009 14:48:34 -0700 Bert Gunter <gunter.ber...@gene.com> wrote: > If generalities -- with the attendant risk of occasional specific caveats > and violations -- can be tolerated, then George Box's (paraphrased) comments > of circa 40-50 years ago seem apropos: why do statisticians obsess over > normality, to which most analyses -- i.e. inference (especially from > balanced designs)-- are robust, when lack of independence of the > observations is the violation of assumptions that can reek the greatest > havoc on the statistical analysis?
While I very much agree with the sentiment, ordinary linear regression is *not* very robust when dealing with very heavy-tailed errors, such as the t-distribution with low degrees of freedom. Of course, one could use 'rlm' instead of 'lm' (and I often prefer to do so), but with proper/better modelling of the error distribution, you will better confidence and prediction intervals. -- Karl Ove Hufthammer ______________________________________________ R-help@r-project.org 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.