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Regression, ANOVA, and the General Linear Model
A Statistics Primer
- Peter Vik - Pacific University, Forest Grove, OR, USA
January 2013 | 344 pages | SAGE Publications, Inc
Peter Vik's Regression, ANOVA, and the General Linear Model: A Statistics Primer demonstrates basic statistical concepts from two different perspectives, giving the reader a conceptual understanding of how to interpret statistics and their use. The two perspectives are (1) a traditional focus on the t-test, correlation, and ANOVA, and (2) a model-comparison approach using General Linear Models (GLM). This book juxtaposes the two approaches by presenting a traditional approach in one chapter, followed by the same analysis demonstrated using GLM. By so doing, students will acquire a theoretical and conceptual appreciation for data analysis as well as an applied practical understanding as to how these two approaches are alike.
Chapter 1: Introduction
Part I: Foundations of the General Linear Model
Chapter 2: Predicting Scores: The Mean and the Error of Prediction
Chapter 3: Bivariate Regression
Chapter 4: Model Comparison: The Simplest Model Versus a Regression Model
Part II: Fundamental Statistical Tests
Chapter 5: Correlation: Traditional and Regression Approaches
Chapter 6: T-test: Concepts and Traditional Approach
Chapter 7: Oneway Analysis of Variance (ANOVA): Traditional Approach
Chapter 8: T-test, ANOVA, and the Bivariate Regression Approach
Part III: Adding Complexity
Chapter 9: Model Comparison II: Multiple Regression
Chapter 10: Multiple Regression: When Predictors Interact
Chapter 11: Two-way ANOVA: Traditional Approach
Chapter 12: Two-way ANOVA: Model Comparison Approach
Chapter 13: One-way ANOVA with Three Groups: Traditional Approach
Chapter 14: ANOVA with Three Groups: Model Comparison Approach
Chapter 15: Two by Three ANOVA: Complex Categorical Models
Chapter 16: Two by Three ANOVA: Model Comparison Approach
Chapter 17: Analysis of Covariance (ANCOVA): Continuous and Categorical Predictors
Chapter 18: Repeated Measures
Chapter 19: Multiple Repeated Measures
Chapter 20: Mixed Between and Within Designs
Appendices
A: Research Designs
B: Variables, Distributions, & Statistical Assumptions
C: Sampling and Sample Sizes
D: Null Hypothesis, Statistical Decision-Making, & Statistical Power
A useful text for students completing a Masters programme and doing a research dissertation. Good level of detail included and step by step process in various statistical tests is easy to follow.
In my opinion slightly too detailed for undergraduates
School of Nursing and Midwifery, National University of Ireland, Galway
May 8, 2013
