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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2 Survival basic concepts
3 Competing risks definitions
4 Descriptive methods for competing risks data
5 Testing a covariate
6 Modelling in the presence of competing risks
7 Calculating the power in the presence of competing risks
8 Other issues in competing risks
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&time applied calculated cause-specific hazard censoring variable CGVHD Chapter CIF estimates clinical coded coef exp(coef competing risk event conditional probability confidence interval covariate crr function cumulative incidence function curves defined delta method discharge from hospital disease failure distant relapse DUC POS endpoint event of interest event of type example 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 number at risk number of events obtained p-value parameter Pepe and Mori Pintilie Practical Perspective presence of competing proc proportional hazards model random relapse and death risks are ignored RT N N score statistic se(coef second malignancy Section standard arm stnum subdensity subdistribution subhazard survival analysis survivor function survtime Table tamoxifen tj≤t tototh treatment tumour type of event variance Wilcoxon test