Measures of Association for Cross Classifications

Measures of Association for Cross Classifications by L. A. Goodman, W. H. Kruskal.

In 1954, prior to the era of modem high speed computers, Leo A. Goodman and William H. Kruskal published the fmt of a series of four landmark papers on measures of association for cross classifications. By describing each of several cross classifications using one or more interpretable measures, the...

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Bibliographic Details
Main Authors: Goodman, L. A. (Author), Kruskal, W. H. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: New York, NY : Springer New York : Imprint: Springer, 1979.
Edition:1st ed. 1979.
Series:Springer Series in Statistics,
Springer eBook Collection.
Subjects:
Statistics .
Probabilities.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Measures of Association for Cross Classifications
  • 1. Introduction
  • 2. Four Preliminary Considerations
  • 3. Conventions
  • 4. Traditional Measures
  • 5. Measures Based on Optimal Prediction
  • 6. Measures Based upon Optimal Prediction of Order
  • 7. The Generation of Measures by the Introduction of Loss Functions
  • 8. Reliability Models
  • 9. Proportional Prediction
  • 10. Association with a Particular Category
  • 11. Partial Association
  • 12. Multiple Association
  • 13. Sampling Problems
  • 14. Concluding Remarks
  • 15. References
  • Measures of Association for Cross Classifications. II: Further Discussion and References
  • 1. Introduction and Summary
  • 2. Supplementary Discussion to Prior Paper
  • 3. Work on Measures of Association in the Late Nineteenth and Early Twentieth Centuries
  • 4. More Recent Publications
  • 5. References
  • Measures of Association for Cross Classifications III: Approximate Sampling Theory
  • 1. Introduction and Summary
  • 2. Notation and Preliminaries
  • 3. Multinominal Sampling over the Whole Double Polytomy
  • 4. Multinomial Sampling within Each Row (Column) of the Double Polytomy
  • 5. Further Remarks
  • 6. References
  • Measures of Association for Cross Classifications IV: Simplification of Asymptotic Variances
  • 1. Introduction and Summary
  • 2. Multinomial Sampling over the Entire Two-Way Cross Classification
  • 3. Independent Multinomial Sampling in the Rows
  • 4. Use of the Results in Practice
  • 5. When Does ?= 0?
  • 6. Cautionary Note about Asymptotic Variances
  • References.

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