Survival Analysis
Springer International Publishing (Verlag)
978-3-030-33438-3 (ISBN)
This book provides an extensive coverage of the methodology of survival analysis, ranging from introductory level material to deeper more advanced topics. The framework is that of proportional and non-proportional hazards models; a structure that is broad enough to enable the recovery of a large number of established results as well as to open the way to many new developments. The emphasis is on concepts and guiding principles, logical and graphical. Formal proofs of theorems, propositions and lemmas are gathered together at the end of each chapter separate from the main presentation.
The intended audience includes academic statisticians, biostatisticians, epidemiologists and also researchers in these fields whose focus may be more on the applications than on the theory. The text could provide the basis for a two semester course on survival analysis and, with this goal in mind, each chapter includes a section with a range of exercises as a teaching aid for instructors.
John O'Quigley is currently INSERM Director of Research at the Laboratory of Probability, Statistics and Modelling, University of Paris - Sorbonne. Earlier positions include that of Director of the Laboratory for Mathematics and Statistics at the Department of Mathematics, University of California San Diego during which time he was also a tenured full professor of mathematics. Professor O'Quigley's academic career began as MRC research scientist at the University of Leeds, U.K., a stint followed by positions at the Fred Hutchinson Cancer Research Center and the Department of Biostatistics, University of Washington, Seattle. Several years were also spent as full professor at the University of Virginia Medical School as well as the Department of Mathematics at Lancaster University, U.K.
Introduction.- Survival analysis.- Survival without covariates.- Proportional hazards models.- Proportional hazards models in epidemiology.- Non-proportional hazards models.- Estimating equations.- Survival given covariate information.- Regression effect process.- Model construction guided by regression effect process.- Hypothesis tests.
| Erscheinungsdatum | 28.04.2021 |
|---|---|
| Reihe/Serie | Springer Series in the Data Sciences |
| Zusatzinfo | XVI, 475 p. 60 illus., 13 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 923 g |
| Themenwelt | Mathematik / Informatik ► Mathematik ► Angewandte Mathematik |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Schlagworte | Cox Model • data structures • epidemiology • Mathematical Modeling • Non parametric statistics • Non-proportional Hazards Models • Proportional Hazards Models • Regression Effect Process • Survival Analysis |
| ISBN-10 | 3-030-33438-4 / 3030334384 |
| ISBN-13 | 978-3-030-33438-3 / 9783030334383 |
| Zustand | Neuware |
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