On 03 Aug 2006 16:32:38 +0200, Peter Dalgaard <[EMAIL PROTECTED]> wrote: > > > > My data consists in 96 groups, each one with 10 observations. Levene's > > > > test suggests that the variances are not equal, and therefore I have > > > > tried to apply the classical transformations to have homocedasticity > > > > in order to be able to use ANOVA. Unfortunately, no transformation > > > > that I have used transforms my data into data with homocedasticity. > > > > The histogram of variances is at > > > > > > > > http://phhs80.googlepages.com/hist1.png > > > > > > > > Is someone able to suggest to me a transformation to overcome the > > > > problem of heterocedasticity? > > > > > > Not based on that information. Try the following instead: > > > > > > fit <- lm(y~g) > > > par(mfrow=c(2,2)); plot(fit) > > > > Thanks, Peter. By 'g', you mean > > > > factor1* factor2*factor3*factor4 > > If that defines your 96 groups, yes.
Thanks, Peter. The result of > fit <- lm(tardiness ~ interaction(factor1,factor2,factor3,factor4)) > par(mfrow=c(2,2)); plot(fit) Warning message: X11 used font size 8 when 7 was requested > is at http://phhs80.googlepages.com/2transform1.png Paul ______________________________________________ R-help@stat.math.ethz.ch 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.
