[R] Looking for transformation to overcome heterogeneity of variances

[Paul Smith]

On 03 Aug 2006 16:32:38 +0200, Peter Dalgaard <p.dalgaard at biostat.ku.dk> 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