Publisher’s description: This is an introduction to the latest arsenal of methods available to students and practicing scientists who undertake longitudinal and other studies that collect repeated measurements for subsequent analysis. The book begins with a development of the general context of repeated measurements. It then describes the three basic types of response variables – continuous (normal), categorical, and count data – and develops a practical framework for creating suitable models and for applying ideas on multivariate distributions and stochastic processes. The book then devotes three sections to examining a large number of concrete examples, including data tables, to illustrate the models available and also includes an extensive list of references. It will interest research statisticians in agriculture, medicine, economics, and psychology, as well as the many consulting statisticians who want an up-to-date expository account of this important topic.
This second edition has been completely updated to take into account the many developments in the area over the last few years. It features 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 software for carrying out the analyses is now available to the public.