Serving as both a student textbook and a professional reference/handbook, this volume explores the statistical methods of examining time intervals between successive state transitions or events. Examples include: survival rates of patients in medical studies, unemployment periods in economic studies, or the period of time it takes a criminal to break the law after his release in a criminological study. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to the specific questions of data organization, to the concrete application of available program packages and the interpretation of the obtained results. Event History Analysis: * makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples * presents the unabbreviated close relationship underlying statistical theory * details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation * discusses specific problems of multi-state and multi-episode models * introduces time-varying covariates and the question of unobserved population heterogeneity * demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.
The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully.
Features • Introduction to survival and event history analysis and how to solve problems with incomplete data using Cox regression. • Parametric proportional hazards models, including the Weibull, Exponential, Extreme Value, and ...
Singer, J. D., & Willett, J. B. (1991). Modeling the days of our lives: Using survival analysis when designing and analyzing longitudinal studies of duration and the timing of events. Psychological Bulletin, 110, 268–290.
This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences.
Publisher Description
The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. T
The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. T
Including new developments and publications which have appeared since the publication of the first edition in 1995, this second edition: *gives a comprehensive introductory account of event history modeling techniques and their use in ...
This book gives the reader a thorough grounding in the subject area and the extensive references at the end of each article provide a comprehensive source of information for further information in more depth.
A fundamental book for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis. Scholars and students can turn to it for teaching and applied needs with confidence.