Thank you very much for the quick answer, I'll try that. The dependence for the other samples are a result of the designs of the studies I want to metaanalyse - most of them are single group studies with pre-post measures.
regards, Markus > I don't see a way to use var.test without data vectors. However, > you could trick it as illustrated by the following: > > SD1 <- SD2 <- N1 <- N2 <- 5 > var.test(SD1*rnorm(N1), SD2*rnorm(N2)) > > For more than two variances, you could use bartlett.test > similarly. However, Bartlett's test, and presumably also var.test, is > highly sensitive to non-normality. I don't have a citation, but I > remember hearing George Box say that Bartlett's test is almost a better > test of non-normality than of inhomogeneity of variance. If you needed > a citation for that, I would look first at various papers and book > sections discussing robustness and Bartlett's test, especially in the > index of Box on Quality and Discovery (Wiley, 2000) or his earlier > collected works volumes. > > This may answer to "independent samples" question. However, we > would need to know more about the nature of the dependence to answer the > dependent samples question, and a sensible answer to the latter may > require untenable assumptions. > > hope this helps. spencer graves > > Markus Koesters wrote: > > >Hello, > > > >for my meta-analysis I try to test if two varainces are equal without > >using the raw scores. I have is the SD's, N's and the Means. > >I want to test the variances from dependent and independend > >samples. > >I assume I can use the var.test procedure for the independent > >samples, but what about the dependent samples ? Has anyone an > >idea how to realise this with R ? > >Thanks in advance > > > >Markus > > > >______________________________________________ > >[EMAIL PROTECTED] mailing list > >https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > > > > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
