Clustering rows and/or columns of a two-way contingency table and a related distribution theory. (English) Zbl 1454.62022

Summary: The row-wise multiple comparison procedure proposed in [C. Hirotsu, Biometrika 70, 579–589 (1983; Zbl 0534.62036)] has been verified to be useful for clustering rows and/or columns of a contingency table in several applications. Although the method improved the preceding work there was still a gap between the squared distance between the two clusters of rows and the largest root of a Wishart matrix as a reference statistic for evaluating the significance of the clustering. In this paper we extend the squared distance to a generalized squared distance among any number of rows or clusters of rows and dissolves the loss of power in the process of the clustering procedure. If there is a natural ordering in columns we define an order sensitive squared distance and then the reference distribution becomes that of the largest root of a non-orthogonal Wishart matrix, which is very difficult to handle. We therefore propose a very nice \(\chi ^{2}\)-approximation which improves the usual normal approximation in [T. W. Anderson, An introduction to multivariate statistical analysis. 3rd ed. Hoboken, NJ: Wiley (2003; Zbl 1039.62044)] and also the first \(\chi ^{2}\)-approximation introduced in [C. Hirotsu, Biometrika 78, No. 3, 583–594 (1991; Zbl 0778.62062)]. A two-way table reported by L. Guttman [“Measurement as structural theory”, Psychometrika 36, 329–347 (1971; doi:10.1007/BF02291362)] and analyzed by M. J. Greenacre [J. Classif. 5, No. 1, 39–51 (1988; Zbl 0652.62053)] is reanalyzed and a very nice interpretation of the data has been obtained.


62-08 Computational methods for problems pertaining to statistics
62H17 Contingency tables
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62J15 Paired and multiple comparisons; multiple testing
Full Text: DOI


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