Accession Number : ADA328382

Title :   The Rank Transformation Test for Balanced Incomplete Block Designs.

Descriptive Note : Final rept.,

Corporate Author : TEXAS TECH UNIV LUBBOCK

Personal Author(s) : Conover, W. J.

PDF Url : ADA328382

Report Date : 24 MAY 1997

Pagination or Media Count : 4

Abstract : In Balanced Incomplete Block Designs the presence of outliers in the data not only indicate non-normality, so that classical methods of analysis on the data are inappropriate, but also diminish the power of classical methods of analysis that assume normality of the data. One alternative is to use Durbin's nonparametric test. This research examined a rank transformation approach where all the data are ranked from smallest to largest, over all treatments and blocks. Then the usual F-test is computed on the ranks. This rank transformation approach is asymptotically distribution-free, and is very powerful in cases where outliers are present as compared with both the parametric F-test and Durbin's nonparametric test. In the case of normality of the data it has only a slight loss of power. Thus it is a good alternative procedure to consider when analyzing data from a Balanced Incomplete Block Design.

Descriptors :   *NONPARAMETRIC STATISTICS, *RANK ORDER STATISTICS, PARAMETRIC ANALYSIS, STATISTICAL PROCESSES, TRANSFORMATIONS.

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE