THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATANOW IN A VALUABLE NEW EDITIONSince publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research.This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data.Features of the Second Edition include:Expanded coverage of interactions and the covariate-adjusted survival functionsThe use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniquesNew discussion of variable selection with multivariable fractional polynomialsFurther exploration of time-varying covariates, complex with examplesAdditional treatment of the exponential, Weibull, and log-logistic parametric regression modelsIncreased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing valuesNew examples and exercises at the end of each chapterAnalyses throughout the text are performed using Stata

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