Synopses & Reviews
Here is an essential 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 presents the general context of repeated measurements and introduces--through a large number of concrete examples, including data tables--the three basic types of response variables: continuous (normal), categorical and count, and duration variables. The ways in which such repeated observations are interdependent, through heterogeneity and time dependence, are discussed. The author also develops a useful framework for constructing suitable models and introduces concepts of multivariate distributions and stochastic processes necessary to appreciate the underpinnings and power of repeated measurements analyses. The book concludes with an extensive bibliography of the repeated measurement literature that will aid readers interested in finding source materials. Written by a distinguished statistician, this book is a much-needed and practical guide to the most current repeated measurements techniques available. It will be welcomed by students, applied statisticians, biostatisticians, biologists, medical researchers, econometricians, sociologists, and psychologists.
Review
"Lindsey's coverage of repeated measures problems arising from continuous, count, categorical, and duration data is plenty broad. . . . The result is a book that is undeniably rich in applications and examples -- drawn mostly from the biological sciences . . .Lindsey's fast-paced, virtuoso model-fitting performance . . ." -- Sociological Methods and Research
Review
"Lindsey's coverage of repeated measures problems arising from continuous, count, categorical, and duration data is plenty broad. . . . The result is a book that is undeniably rich in applications and examples -- drawn mostly from the biological sciences . . .Lindsey's fast-paced, virtuoso
model-fitting performance . . ." -- Sociological MethodsandResearch
Synopsis
Here is an essential 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 presents the general context of repeated measurements and introduces--through a large number of concrete examples, including data tables--the three basic types of response variables: continuous (normal), categorical and count, and duration variables. The ways in which such repeated observations are interdependent, through heterogeneity and time dependence, are discussed. The author also develops a useful framework for constructing suitable models and introduces concepts of multivariate distributions and stochastic processes necessary to appreciate the underpinnings and power of repeated measurements analyses. The book concludes with an extensive bibliography of the repeated measurement literature that will aid readers interested in finding source materials. Written by a distinguished statistician, this book is a much-needed and practical guide to the most current repeated measurements techniques available. It will be welcomed by students, applied statisticians, biostatisticians, biologists, medical researchers, econometricians, sociologists, and psychologists.
Synopsis
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.
Description
Includes bibliographical references (p. [485]-499) and index.
Table of Contents
Notation and symbols
I. INTRODUCTION
1 Basic concepts
2 Fundamentals of modelling
3 Multivariate models
II. CONTINUOUS MEASUREMENTS
4 Heterogeneous populations
5 Longitudinal studies
6 Non-normal responses
III. CATEGORICAL AND COUNT DATA
7 Overdispersion
8 Longitudinal discrete data
IV. DURATION DATA
9 Frailty
10 Event histories
V. PLANNING A STUDY
11 Design issues
12 Modelling missing data and dropouts
APPENDICES
A Data tables for the examples
B Data tables for the exercises
Bibliography
Index