· 2013· Book chapter
Multiple Comparison Procedures
- 2,138citations
- 2013year
Short summary
This paper provides a comprehensive overview of classical and alternative multiple comparison procedures for fixed-effects linear models with normal homoscedastic independent errors, covering single-step, stepwise, and other non-hierarchical families of comparisons.
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Key points
- Covers single-step and stepwise procedures for various comparison types in linear models.
- Addresses MCPs for models with unequal variances and mixed-effects models.
- Includes distribution-free, robust, decision-theoretic, and Bayesian approaches.
- Provides theoretical background and practical considerations for designing experiments with multiple comparisons.
AI-generated from the title and abstract; the full text is not read.
Abstract
PROCEDURES BASED ON CLASSICAL APPROACHES FOR FIXED--EFFECTS LINEAR MODELS WITH NORMAL HOMOSCEDASTIC INDEPENDENT ERRORS. Some Theory of Multiple Comparisons Procedure Fixed--effects Linear Models. Single--step Procedures for Pairwise and More General Comparisons Among All Treatments. Stepwise Procedures for Pairwise and More General Comparisons Among All Treatments. Procedures for Some Other Nonhierarchical Finite Families of Comparisons. Designing Experiments for Multiple Comparisons. PROCEDURES FOR OTHER MODELS AND PROBLEMS, AND PROCEDURES BASED ON ALTERNATIVE APPROACHES. Procedures for One--way Layouts with Unequal Variances. Procedures for Some Mixed--effects Models. Distribution--free and Robust Procedures. Some Miscellaneous Multiple Comparison Problems. Optimal Procedures Using Decision--theoretic, Bayesian, and Other Approaches. Appendixes. Tables. References. Index.
The authors' abstract, as published at the source., 2013 · DOI ↗
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Field: Statistics and Probability
Statistics and ProbabilityMathematics