The Analysis of Variance: Fixed, Random and Mixed Models

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The analysis of variance (ANOYA) models have become one of the most widely used tools of modern statistics for analyzing multifactor data. The ANOYA models provide versatile statistical tools for studying the relationship between a dependent variable and one or more independent variables. The ANOYA mod­ els are employed to determine whether different variables interact and which factors or factor combinations are most important. They are appealing because they provide a conceptually simple technique for investigating statistical rela­ tionships among different independent variables known as factors. Currently there are several texts and monographs available on the sub­ ject. However, some of them such as those of Scheffe (1959) and Fisher and McDonald (1978), are written for mathematically advanced readers, requiring a good background in calculus, matrix algebra, and statistical theory; whereas others such as Guenther (1964), Huitson (1971), and Dunn and Clark (1987), although they assume only a background in elementary algebra and statistics, treat the subject somewhat scantily and provide only a superficial discussion of the random and mixed effects analysis of variance.

Author(s): Hardeo Sahai, Mohammed I. Ageel (auth.)
Edition: 1
Publisher: Birkhäuser Basel
Year: 2000

Language: English
Pages: 742
Tags: Probability Theory and Stochastic Processes; Statistical Theory and Methods; Analysis

Front Matter....Pages i-xxxv
Introduction....Pages 1-9
One-Way Classification....Pages 11-123
Two-Way Crossed Classification Without Interaction....Pages 125-175
Two-Way Crossed Classification with Interaction....Pages 177-280
Three-Way and Higher-Order Crossed Classifications....Pages 281-345
Two-Way Nested (Hierarchical) Classification....Pages 347-394
Three-Way and Higher-Order Nested Classifications....Pages 395-429
Partially Nested Classifications....Pages 431-460
Finite Population and Other Models....Pages 461-482
Some Simple Experimental Designs....Pages 483-542
Analysis of Variance Using Statistical Computing Packages....Pages 543-567
Back Matter....Pages 569-742