title: Exact and resampling probability values for measures of categorical variation and consensus.
abstract: When analyzing categorical data, it is often important to assess the magnitude of variation, or consensus, among observations in unordered categories. Utilizing the theory of partitions, exact solutions for five commonly used measures of categorical variation are presented. When the number of partitions is very large, resampling methods provide close approximations to exact probability values.
authors.affiliation: Department of Sociology, Colorado State University, Fort Collins, CO 80523-1784, USA. janisj@lamar.colostate.edu
authors.forename: Janis E
authors.initials: JE
authors.lastname: Johnston
authors.forename: Kenneth J
authors.initials: KJ
authors.lastname: Berry
authors.forename: Paul W
authors.initials: PW
authors.lastname: Mielke
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D032921:Consensus; D003627:Data Interpretation, Statistical; D006801:Humans; D008432:Mathematical Computing; D011336:Probability; D012494:Sampling Studies; D012984:Software