This second edition of Models for Repeated Measurements has been comprehensively revised and updated, taking into account the huge amount of research that has been carried out in the subject in recent years. A wide variety of useful new models is now available, models that have revolutionized the analysis of such data. The second edition contains three new chapters on models for continuous non-normal data, on various design issues specific to repeated measurements, and on missing data and dropouts. Exercises have been added at the ends of most chapters, and the programming functions needed to carry out the analyses in the book are publicly available. Models for Repeated Measurements is an essential reference for research statisticians in agriculture, medicine, economics, and psychology, and for the many consulting statisticians who want an up-to-date expository account of this important topic. The book is organized into four parts. In the first part, the general context of repeated measurements is presented. The three basic types of response variables, continuous (normal), categorical and count, and duration, are introduced. There is a discussion of the ways in which such repeated observations are interdependent. The book also develops a framework for constructing suitable models, with the introduction of the necessary concepts of multivariate distributions and stochastic processes. In the following three parts, a large number of specific examples, including data tables, is presented to illustrate the models available. Each of these parts corresponds to one of the types of responses mentioned above. FROM REVIEWS OF THE FIRST EDITION . . . a timely book . . . useful both as a graduate text and as a consulting source. Statistical Methods in Medical Research
