Nonparametric Measures of Association / Edition 1

by Jean D. Gibbons Fielden

Overview

When analyzing data, how should the relationship between two or more sets of observations be described, that is, 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, the author clearly describes such techniques as Spearman's rho, Kendall's tau, Goodman and Kruskals' gamma and Somer's d and carefully explains the calculation procedures as well as the substantive meaning of each measure. In addition, each technique is illustrated by one or more examples from recent social or behavioural science studies. Finally, Gibbons provides information on the strengths and weaknesses of leading statisti

Product Details

ISBN-13:	9780803946644
Publisher:	SAGE Publications
Publication date:	02/25/1993
Series:	Quantitative Applications in the Social Sciences , #91
Edition description:	New Edition
Pages:	104
Product dimensions:	5.50(w) x 8.30(h) x 0.30(d)

About the Author

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.”

Table of Contents

Introduction
Spearman's Rho and Kendall's Tau as Descriptive Measures of Association
Inferences Based on Rho and Tau
Kendall's Coefficient of Concordance
Partial Correlation
Measures of Association in Ordered Contingency Tables
Summary