This is a practical, up to date guide to modern methods in the analysis of time to event data. The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health related researchers who study time to event data. This book helps bridge this important gap in the literature. "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.
Key topics covered in depth include: Variable selection; Identification of the scale of continuous covariates; The role of interactions in the model; Interpretation of a fitted model; Assessment of fit and model assumptions; Regression diagnostics; Recurrent event models, frailty models, and additive models; and, Commercially available statistical software and getting the most out of it. "Applied Survival Analysis" is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health related fields.
- ISBN10 0471437328
- ISBN13 9780471437321
- Publish Date 24 January 2003 (first published 21 January 1999)
- Publish Status Out of Stock
- Out of Print 28 August 2008
- Publish Country US
- Imprint John Wiley & Sons Inc
- Format Hardcover
- Pages 648
- Language English