Multiple Comparison Procedures

Offering a balanced, up-to-date view of multiple comparison procedures, this book refutes the belief held by some statisticians that such procedures have no place in data analysis. With equal emphasis on theory and applications, it establishes the advantages of multiple comparison techniques in reducing error rates and in ensuring the validity of statistical inferences. Provides detailed descriptions of the derivation and implementation of a variety of procedures, paying particular attention to classical approaches and confidence estimation procedures. Also discusses the benefits and drawbacks of other methods. Numerous examples and tables for implementing procedures are included, making this work both practical and informative.

Yosef Hochberg, PhD, is Professor in the Department of Statistics and Operations Research at Tel Aviv University, Israel. Dr. Hochberg's areas of research interest include multiple comparisons, categorical data analysis, and medical applications of biostatistical methods.

Ajit C. Tamhane, PhD, is Senior Associate Dean of the McCormick School of Engineering and Applied Science at Northwestern University, where he is also Professor in the Department of Industrial Engineering and Management Sciences. A Fellow of the American Statistical Society, Dr. Tamhane has more than thirty years of academic and consulting experience in the areas of applied and mathematical statistics. He is the author of Statistical Analysis of Designed Experiments: Theory and Applications, also published by Wiley.

Introduction	p. 1
Two Early Multiple Comparison Procedures	p. 2
Basic Notions and Philosophy of Multiple Comparisons	p. 5
Examples	p. 12
Procedures Based in Classical Approaches for Fixed-Effects Linear Models with Normal Homoscedastic Independent Errors	p. 17
Some Theory of Multiple Comparison Procedures for Fixed-Effects Linear Models	p. 17
Single-Step Procedures for Nonhierarchical Families	p. 28
Single-Step Procedures for Hierarchical Families	p. 43
Step-Down Procedures	p. 53
Single-Step Procedures for Pairwise and More General Comparisons among All Treatments	p. 72
Scheffé's S-Procedure	p. 73
Tukey's T-Procedure for Balanced Designs	p. 80
Modifications of the T-Procedure for Unbalanced Designs	p. 85
Comparisons among Single-Step Procedures	p. 102
Additional Topics	p. 107
Stepwise Procedures for Pairwise and More General Comparisons among All Treatments	p. 110
Step-Down Procedures Based on F-Statistics	p. 111
Step-Down Procedures Based in Studentized Range Statistics	p. 114
Peritz's Closed Step-Down Procedure	p. 121
Step-Up Procedures	p. 124
A Comparison of Single-Step and Stepwise Procedures	p. 128
Procedures for Some Nonhierarchical Finite Families of Comparisons	p. 134
Orthogonal Comparisons	p. 135
Comparisons with a Control	p. 139
Comparisons with the "Best" Treatment	p. 150
Two Miscellaneous Families	p. 157
Designing Experiments for Multiple Comparisons	p. 161
Single-Stage Procedures	p. 163
Two-Stage Procedures	p. 171
Incomplete Block Designs for Comparing Treatments with a Control	p. 174
Procedures for Other Models and Problems, and Procedures Based on Alternative Approaches	p. 179
Procedures for One-Way Layouts with Unequal Variances	p. 181
Single-Stage Procedures	p. 182
Two-Stage Procedures	p. 194
Step-Down Procedures	p. 204
Procedures for Mixed Two-Way Layouts and Designs with Random Covariates	p. 207
Procedures for One-Way Repeated Measures and Mixed Two-Way Designs	p. 208
Procedures for Analysis of Covariance Designs with Random Covariates	p. 219
Distribution-Free and Robust Procedures	p. 234
Procedures for One-Way Layouts	p. 235
Procedures for Randomized Complete Block Designs	p. 250
Procedures Based on Other Approaches	p. 267
Robust Procedures	p. 271
Some Miscellaneous Multiple Comparison Problems	p. 274
Multiple Comparison Procedures for Categorical Data	p. 274
Multiple Comparisons of Variances	p. 282
Graphical Procedures	p. 286
Multiple Comparisons of Means under Order Restrictions	p. 290
Interactions in Two-Way Layouts	p. 294
Partitioning Treatment Means into Groups	p. 303
Optimal Procedures Based on Decision-Theoretic, Bayesian, and Other Approaches	p. 310
A Decision-Theoretic Approach	p. 311
A Neyman-Pearson Type Approach	p. 314
A Bayesian Approach	p. 318
A Combined Bayesian and Neyman-Pearson Type Approach	p. 334
A ¿-Minimax Approach	p. 336
Appendixes	p. 341
Some General Theory of Multiple Comparison Procedures	p. 343
Some Probability Inequalities Useful in Multiple Comparisons	p. 362
Some Probability Distributions and Tables Useful in Multiple Comparisons	p. 373
References	p. 417
Author Index	p. 439
Subject Index	p. 445
Table of Contents provided by Publisher. All Rights Reserved.

What is included with this book?

The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

FREE SHIPPING

Amazon no longer offers textbook rentals. We do!

Multiple Comparison Procedures

Summary

Author Biography

Table of Contents

Supplemental Materials