Competing Risks: A Practical Perspective
The need to understand, interpret and analyse competing risk data is key to many areas of science, particularly medical research. There is a real need for a book that presents an overview of methodology used in the interpretation and analysis of competing risks, with a focus on practical applications to medical problems, and incorporating modern techniques. This book fills that need by presenting the most up-to-date methodology, in a way that can be readily understood, and applied, by the practitioner.
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Survival basic concepts
Competing risks definitions
Descriptive methods for competing risks data
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&time 2006 John Wiley applied calculated cause-specific hazard censoring variable CGVHD Chapter CIF estimates clinical competing risk event conditional probability confidence interval covariate crr function cuminc cumulative incidence function curves death due defined delta method discharge from hospital disease failure distant relapse endpoint event of interest event of type example experimental arm exponential distribution Figure follic dataset formula given Gray's test hazard function hazard ratio Hodgkin's disease Kaplan-Meier estimate last follow-up latent failure log-rank test macro marginal distribution Median number of events number of patients obtained p-value parameter Pepe and Mori Pintilie plot Practical Perspective presence of competing proportional hazards model random relapse and death risks are ignored score statistic second malignancy Section standard arm subdensity subdistribution subhazard survival analysis survivor function Table tamoxifen tototh treatment TRUE coefficients tumour two-sided p-values type of event variance Wilcoxon test