[R] Beginner: Homogenity of Variances

Markus Koesters Markus.Koesters at uni-jena.de
Sat Nov 1 17:18:40 CET 2003


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
> >
> >______________________________________________
> >R-help at stat.math.ethz.ch mailing list
> >https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> >  
> >
>




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