Statistical Tests for Mixed Linear Models (Hardcover)
Language: English
Published by John Wiley & Sons Inc, New York, 1998
Series: Book 165 of 358 - Wiley Series in Probability and Statistics
- First Edition
- Hardcover
- New
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
AbeBooks seller since June 29, 2022
Condition: New
£ 170.49
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Hardcover. An advanced discussion of linear models with mixed or random effects. In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models at an advanced level. Statistical Tests for Mixed Linear Models: Combines analysis and testing in one self-contained volume.Describes analysis of variance (ANOVA) procedures in balanced and unbalanced data situations.Examines methods for determining the effect of imbalance on data analysis.Explains exact and optimum tests and methods for their derivation.Summarizes test procedures for multivariate mixed and random models.Enables novice readers to skip the derivations and discussions on optimum tests. Offers plentiful examples and exercises, many of which are numerical in flavor.Provides solutions to selected exercises. Statistical Tests for Mixed Linear Models is an accessible reference for researchers in analysis of variance, experimental design, variance component analysis, and linear mixed models. It is also an important text for graduate students interested in mixed models. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…
Seller Inventory # 9780471156536
- Title
- Statistical Tests for Mixed Linear Models (Hardcover)
- Author
- Bimal K. Sinha
- Publisher
- John Wiley & Sons Inc, New York
- Publication year
- 1998
- Condition
- new
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 0471156531
- ISBN 13
- 9780471156536
- Edition
- 1st Edition
- Series
- Book 165 of 358: Wiley Series in Probability and Statistics
In recent years a breakthrough has occurred in our ability to draw inferences from exact and optimum tests of variance component models, generating much research activity that relies on linear models with mixed and random effects. This volume covers the most important research of the past decade as well as the latest developments in hypothesis testing. It compiles all currently available results in the area of exact and optimum tests for variance component models and offers the only comprehensive treatment for these models at an advanced level.
Statistical Tests for Mixed Linear Models:
- Combines analysis and testing in one self-contained volume.
- Describes analysis of variance (ANOVA) procedures in balanced and unbalanced data situations.
- Examines methods for determining the effect of imbalance on data analysis.
- Explains exact and optimum tests and methods for their derivation.
- Summarizes test procedures for multivariate mixed and random models.
- Enables novice readers to skip the derivations and discussions on optimum tests. Offers plentiful examples and exercises, many of which are numerical in flavor.
- Provides solutions to selected exercises.
Statistical Tests for Mixed Linear Models is an accessible reference for researchers in analysis of variance, experimental design, variance component analysis, and linear mixed models. It is also an important text for graduate students interested in mixed models.
"Synopsis" may belong to another edition of this title.
About the Author
Thomas Mathew and Bimal K. Sinha are Professors of Statistics at the University of Maryland. Professor Sinha is coauthor of Robustness of Statistical Tests.
"About the title" may belong to another edition of this title.
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