This compact and highly readable volume presents Spearman′s and Kendall′s rank correlation and coefficients, Kendall′s coefficients of concordance and of partial correlation, and several association measures for ordered contingency tables. . . . This inexpensive and lucid text offers a good introduction, or a quick review, of methods of rank correlation. It should prove beneficial to the practitioner who selects from and interprets the many measures produced by modern statistical packages. --Journal of the American Statistical Association When analyzing your data, how should you describe the relationship (or, association) between two or more sets of observations, i.e., values of two or more variables, when the variables are ordinal and not bivariate normal? Aimed at helping the researcher select the most appropriate measure of association for two or more variables, Jean Dickinson Gibbons clearly describes such techniques as Spearman′s rho, Kendall′s tau, Goodman & Kruskals′ gamma, and Somer′s d. She also carefully explains the calculation procedures as well as the substantive meaning of each measure (such as that rho is based on rankings while tau is based on paired comparisons). In addition, each technique is illustrated by one or more examples from recent social or behavioral science studies. Lastly, Gibbons provides information on the strengths and weaknesses of leading statistical packages for calculating these measures.
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Gibbons, a retired professor from the University of Alabama who now lives in Florida, earned her Ph.D. in statistics from Virginia Tech in 1962. She says she made the gift as an effort to enable the university to recruit the nation’s best doctoral candidates in her field, and to help the United States remain the global leader in the discipline.
“Statistics is my love,” Gibbons said. “It’s my vocation, as well as my avocation. I was so delighted when I discovered statistics … and I think that it is a field that will always be of utmost importance.”
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