Comparison Between Continuous-Time and Discrete-Time: Event History Analysis with Stata

Blossfeld, Gwendolin J.

ISBN 10: 1032717386 / ISBN 13: 9781032717388

Published by Routledge, 2025

About this Item

Seller Inventory # V9781032717388

Bibliographic Details

• Title: Comparison Between Continuous-Time and Discrete-Time: Event History Analysis with Stata
• Publisher: Routledge
• Publication Date: 2025
• Language: English
• ISBN 10: 1032717386
• ISBN 13: 9781032717388
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Comparison Between Continuous-Time and Discrete-Time: Event History Analysis with Stata elucidates the statistical concepts and empirical applications of both continuous-time and discrete-time event history models. Empirical scientists have increasingly collected data on the timing of events, with the understanding that events can occur at any point in time and may be recorded using different observation schemes. However, time-continuous processes are not always observed with fine-grained temporal resolution; in some cases, they are captured with larger observation intervals (monthly, yearly, biennially, and quadrennially).

This book introduces the need for discrete-time event history analysis methods and adeptly discusses the limitations of the discrete-time approach when compared to continuous-time models. It offers an in-depth comparison of both methods and sheds light on how they differ and align. By utilizing the statistical software Stata and using a campus example data set, the book provides practical examples that showcase the implications of larger observation intervals in discrete-time applications.

This book serves as an essential resource for researchers, students, and practitioners seeking to comprehend the nuances of event history analysis in both continuous and discrete-time frameworks. Its comprehensive exploration of statistical techniques and real-world applications will equip readers with a deeper understanding of the strengths and limitations of each method, thus enabling more informed and robust decision-making in empirical research.

About the Author

Gwendolin J. Blossfeld is Postdoc at the Faculty of Social Sciences, Economics and Business Administration at the University of Bamberg, Germany. Her research interests are in the areas of longitudinal analysis methods, life course research, longitudinal data collection, causal analysis, sociology of education, labor market research, social inequality, demography, migration, and gender studies. She has published five books and several peer-reviewed journal articles.