Applied Survival Analysis Regression Modeling of Time to Event Data

Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields Recent years have seen a major growth in the development of methods for analyzing survival time data. At the same time, there has been little in the statistical literature to guide researchers in health-related areas who study time to event data. Applied Survival Analysis fills this gap, providing a comprehensive, self-contained introduction to regression modeling used in the analysis of time to event data in epidemiological, biostatistical, and other health-related research. In any applied setting, a statistical analysis should begin with a thoughtful and thorough univariate description of the data.