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Survival Analysis: Proportional and Non-Proportional Hazards Regression /
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Catalogue Information
Field name
Details
Dewey Class
003.3
Title
Survival Analysis ([EBook] :) : Proportional and Non-Proportional Hazards Regression / / by John O'Quigley.
Author
O'Quigley, John
Other name(s)
SpringerLink (Online service)
Edition statement
1st ed. 2021.
Publication
Cham : : Springer International Publishing : : Imprint: Springer, , 2021.
Physical Details
XVI, 475 p. 60 illus., 13 illus. in color. : online resource.
ISBN
9783030334390
Summary Note
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. .:
Contents note
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.
Mode of acces to digital resource
Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site
https://doi.org/10.1007/978-3-030-33439-0
Links to Related Works
Subject References:
Applied Statistics
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Artificial intelligence—Data processing
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Bayesian Inference
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Data Science
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Mathematical Modeling and Industrial Mathematics
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Mathematical models
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Probabilities
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Probability Theory
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Statistics
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Authors:
author
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O'Quigley, John
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Corporate Authors:
SpringerLink (Online service)
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Classification:
003.3
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