Traditional approaches to ANOVA and ANCOVA are now being replaced by a General Linear Modeling (GLM) approach. This book begins with a brief history of the separate development of ANOVA and regression analyses and demonstrates how both analysis forms are subsumed by the General Linear Model. A simple single independent factor ANOVA is analysed first in conventional terms and then again in GLM terms to illustrate the two approaches.

The text then goes on to cover the main designs, both independent and related ANOVA and ANCOVA, single and multi-factor designs. The conventional statistical assumptions underlying ANOVA and ANCOVA are detailed and given expression in GLM terms.

Alternatives to traditional ANCOVA are also presented when circumstances in which certain assumptions have not been met. The book also covers other important issues in the use of these approaches such as power analysis, optimal experimental designs, normality violations and robust methods, error rate and multiple comparison procedures and the role of omnibus F-tests.

Autorentext

Andrew is Senior Lecturer at the University of Keele.

Inhalt

An Introduction to Analysis of Variance, Analysis of Covariance and General Linear Models
An Introduction to General Linear Models
Regression, Analysis of Variance and Analysis of Covariance
Traditional and GLM Approaches to Independent Measures Single Factors Anova Designs
GLM Approaches to Independent Measures Factorial Anova Designs
GLM Approaches to Repeated Measures Design
GLM Approaches for Factorial Repeated Measures Designs
The GLM Approach to Ancova
Assumptions Underlying Anova, Traditional Ancova and GLMs
Some Alternatives to Traditional Ancova
Further Issues in Anova and Ancova