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. I need to compute an error amount for ANOVA or find a nonparametric equivalent.
Thanks, William -- View this message in context: http://r.789695.n4.nabble.com/Problems-with-normality-req-for-ANOVA-tp2310275p2310275.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.
