Modelling Survival Data in Medical Research 4th Edition

Capture the complexities of time-to-event analysis with Modelling Survival Data in Medical Research, 4th Edition by David Collett — an authoritative, accessible guide for clinicians, biostatisticians, and researchers worldwide. This edition sharpens core concepts while bringing contemporary modelling approaches into clear focus, helping you convert clinical questions into robust statistical answers.

Start with intuitive explanations of Kaplan–Meier curves and hazard functions, then progress to in-depth treatments of Cox proportional hazards models, parametric survival models, competing risks, and frailty models. Practical examples and step-by-step worked problems illuminate model selection, interpretation of hazard ratios, handling censored data, and assessing model fit — all framed around real clinical research scenarios and trials.

Whether you’re designing a study, analysing clinical trial outcomes, or interpreting survival results for publication, this book balances theory with practice. Its lucid style demystifies complex topics without sacrificing rigor, making it ideal for postgraduate students, clinical investigators, and practising statisticians. Clear explanations help readers apply models to diverse settings — from oncology and cardiology trials to epidemiological follow-up studies.

If you need a dependable reference that bridges methodological detail and practical application, this fourth edition delivers. Enhance your analytical toolkit and improve the quality of your time-to-event analyses — indispensable for research teams and institutions across the UK, US, Europe, and beyond. Order your copy today and bring clarity and confidence to survival analysis in medical research.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.