Buch, Englisch, 124 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 2234 g
Reihe: SpringerBriefs in Statistics
Buch, Englisch, 124 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 2234 g
Reihe: SpringerBriefs in Statistics
ISBN: 978-3-662-49331-1
Verlag: Springer
Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further studies in semiparametric and nonparametric theories, counting process models, study designs in epidemiology, and the development of many other regression models that could offer more flexible or more suitable approaches in data analysis.
Flexible semiparametric regression models are increasingly being used to relate lifetime distributions to time-dependent explanatory variables. Throughout the book, various recent statistical models are developed in close connection with specific data from experimental studies in clinical trials or from observational studies.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Biomedizin, Medizinische Forschung, Klinische Studien
- Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Epidemiologie, Medizinische Statistik
Weitere Infos & Material
Introduction: Several Classical Data Examples for Survival Analysis.- Elements of Survival Analysis.- The Cox Proportional Hazards Model.- The AFT, GPH, LT, Frailty, and GLPH Models.- Cross-effect Models of Survival Functions.- The Simple Cross-effect Model.- Goodness-of-Fit for the Cox Model.- Remarks on Computations in Parametric and Semiparametric Estimation.- Cox Model for Degradation and Failure Time Data.- References.- Index.