Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence / Edition 1

From the Publisher

"The book begins with an excellent introduction to the types of questions that might be answered by a longitudinal study...After a chapter with sensible suggestions for exploratory analysis... --Statistics in Medicine Review

"It will come as no surprise to those familiar with Judith Singer and John Willett's didactic journal articles to learn that they have written a terrific textbook on longitudinal data analysis." --Social Methods and Research

"Anyone teaching courses on the analysis of repeated measures data or on the analysis of survival data in the social sciences will find this book extremely helpful. It is thorough, well written and the associated web site (www.oup-usa.org/alda) provides useful back-up material in the form of datasets used in the book..." --Centre for Multilevel Modelling

"This book...will certainly have a substantial impact on the analyses of longitudinal data carried out in many fields." --International Epidemiological Association

"Longitudinal data are often essential for understanding the dynamics of social and other systems. Recent methodological developments in multilevel and event history data modeling have made it possible to handle such data efficiently and informatively. This book provides a valuable exploration of the application of this methodology, within a likelihood framework, to real data using careful and clear descriptions of procedures. Particularly important is the attention given by the authors to the assumptions built into their statistical models. This book will provide a useful resource for the applied researcher who wishes to gain insight into the analysis of longitudinal data and to be guided through the various stages of an analysis."-Harvey Goldstein, Professor of Statistical Methods, University of London, Institute of Education

"This book will be of great use to many behavioral and social researchers who use quantitative methods to analyze longitudinal data. Its defining contribution is that it teaches researchers to analyze data wisely. Through many examples, it helps people look at their data using a variety of graphical and tabular techniques. It encourages people to formulate sensible models in light of their research questions. It teaches people to view such models as tentative representations, subject to criticism and revision based on data. It wages a much-needed struggle against overly formulaic thinking that is all too common in the every day practice of statistical analysis in social science."-Stephen W. Raudenbush, Professor of Education and Statistics, Senior Research Scientist, Survey Research Center, School of Education, University of Michigan

"This is a clearly written book on longitudinal analysis, multilevel models, and survival analysis by two outstanding classroom teachers. Building systematically from elementary ideas to advanced data analysis, it will be a great resource for students and investigators in the social and biomedical sciences."-James H. Ware, Frederick Mosteller Professor of Biostatistics, Harvard School of Public Health

"...provides readers with a solid, thorough, andaccurate understanding of concepts and procedures.[S[ubstantive researchers may have been introduced to multilevel models or methods for categorical data analysisbut they have difficulty seeing how these methods can be applied to longitudinal data. The authors make this connection, and also comprehensively introduce the methods to those completely unfamiliar with either multilevel models or survival analysis."--Journal of the American Statistical Association, March 2005, vol. 100, No. 469, 352-353