Survival Analysis: A New Guide for Social Scientists

Survival analysis is used by quantitative social scientists to understand the forces that determine the duration of events, particularly in non-proportional covariate effects, competing risks, and multi-state models. It promotes multi-state models as a unified framework and highlights the role of general transition probabilities as key quantities of interest for policy interventions.

Format: Paperback / softback
Length: 75 pages
Publication date: 26 May 2022
Publisher: Cambridge University Press

Survival analysis is a crucial tool employed by quantitative social scientists to delve into the intricate forces that govern the duration of events. By employing this fundamental element, researchers gain valuable insights into the factors that shape the longevity of various phenomena. This comprehensive guide offers a roadmap for emerging techniques and models in survival analysis, with a particular emphasis on three key areas: non-proportional covariate effects, competing risks, and multi-state models. Moreover, it revisits models for repeated events, providing valuable perspectives on their application and limitations.

One of the central tenants of survival analysis is the promotion of multi-state models as a unified framework for this field. These models allow researchers to account for the transitions between different states or conditions that individuals or units may experience over time. By incorporating general transition probabilities as key quantities of interest, survival analysis becomes more comprehensive and nuanced. These probabilities capture the long-term probabilities that units will occupy particular states conditional on their current state, thereby providing a deeper understanding of the dynamics at play.

In essence, survival analysis serves as a powerful tool for researchers seeking to unravel the complexities of event duration. By employing advanced techniques and models, researchers can gain a deeper understanding of the factors that influence survival outcomes, inform policy interventions, and make informed decisions based on empirical evidence. The significance of survival analysis lies in its ability to provide a comprehensive framework for analyzing and interpreting data, enabling researchers to make meaningful contributions to the field of social sciences.

Weight: 138g
Dimension: 151 x 229 x 9 (mm)
ISBN-13: 9781009054508