Title
A permutation procedure for testing the equality of pattern hypotheses across groups involving correlation or covariance matrices
Abstract
This paper describes a permutation procedure to test for the equality of selected elements of a covariance or correlation matrix across groups. It involves either centring or standardising each variable within each group before randomly permuting observations between groups. Since the assumption of exchangeability of observations between groups does not strictly hold following such transformations, Monte Carlo simulations were used to compare expected and empirical rejection levels as a function of group size, the number of groups and distribution type (Normal, mixtures of Normals and Gamma with various values of the shape parameter). The Monte Carlo study showed that the estimated probability levels are close to those that would be obtained with an exact test except at very small sample sizes (5 or 10 observations per group). The test appears robust against non-normal data, different numbers of groups or variables per group and unequal sample sizes per group. Power was increased with increasing sample size, effect size and the number of elements in the matrix and power was decreased with increasingly unequal numbers of observations per group.
Year
DOI
Venue
2000
10.1023/A:1008943611855
Statistics and Computing
Keywords
Field
DocType
permutation test,equality of correlation matrices,covariance matrices
Monte Carlo method,Combinatorics,Estimation of covariance matrices,Matrix (mathematics),Permutation,Covariance matrix,Statistics,Resampling,Mathematics,Sample size determination,Covariance
Journal
Volume
Issue
ISSN
10
3
1573-1375
Citations 
PageRank 
References 
0
0.34
0
Authors
1
Name
Order
Citations
PageRank
Bill Shipley100.34