The General Linear Model

General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data analysis. This volume fills this void by introducing the General Linear Model (GLM), whose basic concept is that an observed variable can be explained from weighted independent variables plus an additive error term that reflects imperfections of the model and measurement error. It also covers multivariate regression, analysis of variance, analysis under consideration of covariates, variable selection methods, symmetric regression, and the recently developed methods of recursive partitioning and direction dependence analysis. Each method is formally derived and embedded in the GLM, and characteristics of these methods are highlighted. Real-world data examples illustrate the application of each of these methods, and it is shown how results can be interpreted.

Author: Alexander Von Eye, Wolfgang Wiedermann
Publisher: Cambridge University Press
Published: 06/29/2023
Pages: 125
Binding Type: Hardcover
Weight: 0.81lbs
Size: 8.50h x 5.50w x 0.50d
ISBN13: 9781009322171
ISBN10: 1009322176
BISAC Categories:
- Psychology | Research & Methodology
- Mathematics | Probability & Statistics | General