This updated textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models.

Updated version of a classic textbook in Statistics Focus on Fisherian inference, rather than the previous blend of Fisherian and NeymanPearson inference Illustrates the practical application of the projective approach to linear models Includes supplementary material: sn.pub/extras

Autorentext

Ronald Christensen is Professor of Statistics at the University of New Mexico, Fellow of the American Statistical Association (ASA) and the Institute of Mathematical Statistics, and former Chair of the ASA Section on Bayesian Statistical Science.

Inhalt
Introduction.- Estimation.- Testing.- One-Way ANOVA.- Multiple Comparison Techniques.- Regression Analysis.- Multifactor Analysis of Variance.- Experimental Design Models.- Analysis of Covariance.- General Gauss-Markov Models.- Split Plot Models.- Mixed Models and Variance Components.- Model Diagnostics.- Variable Selection.- Collinearity and Alternative Estimates.-