This 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, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate- level course. All of the standard topics are covered in depth: ANOVA, estimation including Bayesian estimation, hypothesis testing, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, variance component estimation, best linear and best linear unbiased prediction, collinearity, and variable selection. This new edition includes discussion of identifiability and its relationship to estimability, different approaches to the theories of testing parametric hypotheses and analysis of covariance, additional discussion of the geometry of least squares estimation and testing, new discussionof models for experiments with factorial treatment structures, and a new appendix on possible causes for getting test statistics that are so small as to be suspicious. Ronald Christensen is a Professor of Statistics at the University of New Mexico. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.
This well-written and interesting book can serve as a textbook for a graduate-level course in linear model theory and its applications, and as a reference book for a wide range of definitions and results associated with particular linear models. Journal of the American Statistical Assoc. "The following quotations are taken from the (same) reviewer's comments on the second edition (Short Book Rezensions, Vol.17/1, April 1997, p.4): The book "retains its fairly mathematical character... The writing style is inviting... friendly and affable... The computing aspects of regression are de-emphasized and the text leans more towards well-prepared students." All are still true, and I once again recommend the book for the indicated target audience." ISI Short Book Rezensions, Vol. 22/3,.
From the reviews of the fourth edition:
"Researchers and students interested in linear statistical models. ... I admire Christensen's very personal and somehow easy-going writing style. ... All in all, Christensen's fourth edition is an excellent course and reference book ... ." (Simo Puntanen, International Statistical Review, Vol. 79 (3), 2011)
"Researchers and students interested in linear statistical models. ... I admire Christensen's very personal and somehow easy-going writing style. ... All in all, Christensen's fourth edition is an excellent course and reference book ... ." (Simo Puntanen, International Statistical Review, Vol. 79 (3), 2011)