Taylor & Francis Ltd Paperback English
Comparison Between Continuous-Time and Discrete-Time
Event History Analysis with Stata
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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 these methods and sheds light on how they differ and align. By utilizing Stata and 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.
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 these methods and sheds light on how they differ and align. By utilizing Stata and 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.