kendall.w {concord}R Documentation

Kendall's W coefficient of concordance

Description

calculates Kendall's W coefficient of concordance

Usage

 kendall.w(x,lambda,descending=TRUE,ranks=FALSE)

Arguments

x matrix of scores or ranks
lambda optional contrast coefficient vector or matrix
descending whether high (default) or low scores represent top ranks
ranks whether the values in x are scores or ranks

Details

kendall.w will accept either a matrix or data frame of scores or ranks where the rows represent methods (usually raters) and the columns represent data objects. It will handle ties, but not missing values. By default it assumes that numerically higher scores represent numerically lower ranks. A vector or matrix of contrast coefficients (which each must sum to zero) may be supplied. A z-score approximation of the significance of each contrast will be displayed if lambda is present. The ranks argument allows the user to pass ranks directly to the function. If ranks are passed without setting ranks to TRUE and with descending TRUE, the order of the ranks will be reversed. For small values of k (methods), kendall.w will try to lookup the tabled values for significance. For k greater than 7, a chi-squared approximation is returned. Only one of these values will be returned.

Value

W value of W
p.table whether the obtained W exceeded the table value for small N
p.chisq the probability of the obtained chi-squared value for larger N

Note

Kendall's W may not be appropriate for nominal class data.

Author(s)

Jim Lemon

References

Siegel, S. & Castellan, N.J.Jr. (1988) Nonparametric statistics for the behavioral sciences. Boston, MA: McGraw-Hill.

See Also

kripp.alpha,cohen.kappa

Examples

 # fictional rankings of job applicants
 app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE)
 # Test the hypothesis that the first three applicants are ranked higher
 # than the last three.
 lambda<-c(1,1,1,-1,-1,-1)
 print(kendall.w(app.mat,lambda))

[Package concord version 1.4-9 Index]