Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance

摘要

When asked if I would review this recently published introductory text on mixed modeling, I accepted with pleasure, and with a sense of curiosity to see how the author tackled this rather challenging, broad subject. The term "mixed modeling" is used here to refer to linear models that have both fixed and random effects. The preface provides an excellent summary of the basic concepts of a mixed model, and how these models form a natural extension of regression and analysis of variance techniques. The introductory chapter then motivates the necessity (at times) of including an additional random effect term beyond the usual error term through the use of a regression example. One of the main strengths of the text is the bridge it provides between traditional analysis of variance (ANOVA) and regression models and the more recently developed class of mixed models.