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Date:         Fri, 11 Feb 2005 09:15:22 +0000
Reply-To:     Jeremy Miles <>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Jeremy Miles <>
Subject:      Re: Statistics Question
Comments: To: Marta García-Granero <>
In-Reply-To:  <>
Content-Type: text/plain; charset="iso-8859-1"; format=flowed

At 08:48 11/02/2005, Marta García-Granero wrote: >Hi > >MK> Yours is a good example of the fact that ANOVA is not nearly >MK> as robust against violations of normality as is often believed, >MK> e.g., in my own field of social psychology. ANOVA is fairly robust >MK> against violations of kurtosis, but is much more sensitive toward >MK> violations of symmetry. > >I have read just the opposite. ANOVA is considered to be quite robust >against violations of symmetry (as a matter of fact, Levene test is an >ANOVA on the absolute values of the residuals, with are really >assymetric). On the other hand, high kurtosis lowers efficiency (not >validity) of the ANOVA. High kurtosis happens when outliers are >present (standard deviation is increased, and p values too). Non >parametric methods handle outliers quite well (replacing them by the >lowest/highest ranks), that's why they give better results for >leptokurtic distributions.

Rand Wilcox has done a lot of work on this. If you are interested, have a look at, for example, Introduction to Robust Estimation and Hypothesis Testing, by Wilcox, published by Acadmic Press, or his paper:

Wilcox, R. R (1998). How many discoveries have been lost by ignoring modern statistical methods? American Psychologist, 53 (3), 300-314.


Jeremy Miles Dept of Health Sciences (Area 4), University of York, York, YO10 5DD Phone: 01904 321375 Mobile: 07941 228018 Fax 01904 321320

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