Models for Repeated Measurments
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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
Models for Repeated Measurements 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 edition of this successful book 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. 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. The book also includes an extensive list of references.
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