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  • Print publication year: 2006
  • Online publication date: December 2009

K

Summary

Kaiser's rule: A rule often used in principal components analysis for selecting the appropriate number of components. When the components are derived from the correlation matrix of the observed variables, the rule advocates retaining only those components with variances greater than unity. See also scree plot. [Everitt, B. S. and Dunn, G., 2001, Applied Multivariate Data Analysis, 2nd edn, Arnold, London.]

Kaplan―Meier estimator: See product limit estimator.

Kappa coefficient: A chance-corrected index of the agreement between, for example, judgements or diagnoses made by two raters. Calculated as the ratio of the observed excess over chance agreement to the maximum possible excess over chance, the coefficient takes the value unity when there is perfect agreement and the value zero when observed agreement is equal to chance agreement. Chance agreement is agreement calculated according to the marginal totals of each rater for each diagnostic category. See also Aickin's measure of agreement and weighted kappa. [Journal of Clinical Epidemiology, 1988, 41, 949–58.]

Karnofsky rating scale: A measure of the ability to cope with everyday activities. The scale has 11 categories ranging from 0 (dead) to 10 (normal, no complaints, no evidence of disease). See also Barthel index. [Neurosurgery, 1995, 36, 270–4.]

Kendall's coefficient of concordance: Synonym for coefficient of concordance.

Kendall's tau statistic: A range of correlation coefficients that use only the ranks of the observations in a data set. See also phi-coefficient. [Everitt, B. S. and Palmer, C., eds., 2005, Encyclopedic Companion to Medical Statistics, Arnold, London.]