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Permutation statistical methods Measures of relationship Janis E. Johnston, Kenneth J. Berry, Michael A. Long
Springer Nature - Springer Mathematics and Statistics (R0) eBooks 2026 English International Available online
View online- Format:
- Book
- Author/Creator:
- Johnston, Janis E., 1957- author.
- Berry, Kenneth J., author.
- Long, Michael A., author.
- Series:
- SpringerBriefs in statistics
- SpringerBriefs in statistics 2191-5458
- Language:
- English
- Subjects (All):
- Mathematical statistics.
- Permutations.
- Nonparametric statistics.
- Physical Description:
- 1 online resource
- Place of Publication:
- Cham, Switzerland Springer [2026]
- Summary:
- "This book gives a concise overview of measures of relationship, including measures of nominal-nominal association, ordinal-ordinal association, interval-interval correlation, nominal-ordinal association, nominal-interval association, ordinal-interval association, and agreement. The book emphasizes permutation statistical methods under the Fisher--Pitman model. However, the permutation analyses are always paired with conventional statistical analyses under the classical Neyman--Pearson model. The pairing allows for comparisons and contrasts between permutation and conventional analyses. Example analyses highlight the differences between the various measures and the permutation and conventional probability values. This book is a companion volume to Permutation Statistical Methods: Tests of Differences by the same authors"-- Springer Nature Link
- Contents:
- Permutation statistical methods
- Measures of nominal association
- Measures of ordinal association
- Measures of correlation
- Mixed measures of association
- Notes:
- Includes bibliographical references and index
- Online resource; title from PDF title page (Springer Nature Link, viewed July 28, 2026)
- Other Format:
- Print version Johnston, Janis E., 1957- Permutation statistical methods
- ISBN:
- 9783032266088
- 3032266084
- OCLC:
- 1608183948
- Access Restriction:
- Restricted for use by site license
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