David et. al: I take issue with this. It is the lack of independence that is the major issue. In particular, clustering, split-plotting, and so forth due to "convenience order" experimentation, lack of randomization, exogenous effects like the systematic effects due to measurement method/location have the major effect on inducing bias and distorting inference. Normality and unequal variances typically pale to insignificance compared to this.
Obviously, IMHO. Note 1: George Box noted this at least 50 years ago in the early '60's when he and Jenkins developed arima modeling. Note 2: If you can, have a look at Jack Youden's classic paper "Enduring Values", which comments to some extent on these issues, here: http://www.jstor.org/pss/1266913 Cheers, Bert Bert Gunter Genentech Nonclinical Biostatistics On Mon, Aug 2, 2010 at 10:32 AM, David Winsemius <dwinsem...@comcast.net>wrote: > > On Aug 2, 2010, at 9:33 AM, wwreith wrote: > > >> I am conducting an experiment with four independent variables each of >> which >> has three or more factor levels. The sample size is quite large i.e. >> several >> thousand. The dependent variable data does not pass a normality test but >> "visually" looks close to normal so is there a way to compute the affect >> this would have on the p-value for ANOVA or is there a way to perform an >> nonparametric test in R that will handle this many independent variables. >> Simply saying ANOVA is robust to small departures from normality is not >> going to be good enough for my client. >> > > The statistical assumption of normality for linear models do not apply to > the distribution of the dependent variable, but rather to the residuals > after a model is estimated. Furthermore, it is the homoskedasticity > assumption that is more commonly violated and also greater threat to > validity. (And if you don't already know both of these points, then you > desperately need to review your basic modeling practices.) > > > I need to compute an error amount for >> ANOVA or find a nonparametric equivalent. >> > > You might get a better answer if you expressed the first part of that > question in unambiguous terminology. What is "error amount"? > > For the second part, there is an entire Task View on Robust Statistical > Methods. > > -- > > David Winsemius, MD > West Hartford, CT > > > ______________________________________________ > 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<http://www.r-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ 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.
