Statistical Tests for Mixed Linear Models / Edition 1

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Overview

Unlike other books on variance components, Statistical Tests for Mixed Linear Models continues beyond point estimation to cover hypothesis and data testing. By addressing these areas, the author presents practical applications of variance component models through testing of fixed effects and variance components. The book showcases research from the past ten years, up to and including current investigations in this field.
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Editorial Reviews

From the Publisher
"...compiles the available results in this area into a single volume." (Quarterly of Applied Mathematics, Vol. LIX, No. 3, September 2001)

"...the authors are to be congratulated for this important and useful book...the authors state...'it will contribute to the development of the area, and enhance its exposure and usefulness.' The reviewers agree." (Mathematical Geology)

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Product Details

Meet the Author

Andre I. Khuri, PhD, is Professor of Statistics at the University of Florida in Gainesville and author of Advanced Calculus with Applications in Statistics and Response Surfaces: Designs and Analyses.

Thomas Mathew and Bimal K. Sinha are Professors of Statistics at the University of Maryland. Professor Sinha is coauthor of Robustness of Statistical Tests.

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Table of Contents

Nature of Exact and Optimum Tests in Mixed Linear Models.

Balanced Random and Mixed Models.

Measures of Data Imbalance.

Unbalanced One-Way and Two-Way Random Models.

Random Models with Unequal Cell Frequencies in the Last Stage.

Tests in Unbalanced Mixed Models.

Recovery of Inter-Block Information.

Split-Plot Designs Under Mixed and Random Models.

Tests Using Generalized P-Values.

Multivariate Mixed and Random Models.

Appendix.

General Bibliography.

Indexes.

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