Modelling Multivariate Survival Data Using Semiparametric Models

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Modelling Multivariate Survival Data Using Semiparametric Models

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Author : 李友榮
language : en
Publisher: Open Dissertation Press
Release Date : 2017-01-27

Modelling Multivariate Survival Data Using Semiparametric Models written by 李友榮 and has been published by Open Dissertation Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with categories.

This dissertation, "Modelling Multivariate Survival Data Using Semiparametric Models" by 李友榮, Yau-wing, Lee, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. DOI: 10.5353/th_b4257528 Subjects: Survival analysis (Biometry) Multivariate analysis Medicine - Research - Statistical methods

Modelling Multivariate Survival Data Using Semiparametric Models

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Author : Yau-wing Lee
language : en
Publisher:
Release Date : 2000

Modelling Multivariate Survival Data Using Semiparametric Models written by Yau-wing Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Medicine categories.

Analysis Of Multivariate Survival Data

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Author : Philip Hougaard
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Analysis Of Multivariate Survival Data written by Philip Hougaard and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.

Survival data or more general time-to-event data occur in many areas, including medicine, biology, engineering, economics, and demography, but previously standard methods have requested that all time variables are univariate and independent. This book extends the field by allowing for multivariate times. As the field is rather new, the concepts and the possible types of data are described in detail. Four different approaches to the analysis of such data are presented from an applied point of view.

Parametric And Semiparametric Models With Applications To Reliability Survival Analysis And Quality Of Life

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Author : M.S. Nikulin
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Parametric And Semiparametric Models With Applications To Reliability Survival Analysis And Quality Of Life written by M.S. Nikulin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields. Specific topics covered include: * cancer prognosis using survival forests * short-term health problems related to air pollution: analysis using semiparametric generalized additive models * semiparametric models in the studies of aging and longevity This book will be of use as a reference text for general statisticians, theoreticians, graduate students, reliability engineers, health researchers, and biostatisticians working in applied probability and statistics.

Survival Analysis In Medicine And Genetics

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Author : Jialiang Li
language : en
Publisher: CRC Press
Release Date : 2013-06-04

Survival Analysis In Medicine And Genetics written by Jialiang Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-04 with Mathematics categories.

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional survival data. It provides thorough coverage of recent statistical developments in the medical and genetics fields. The text mainly addresses special concerns of the survival model. After covering the fundamentals, it discusses interval censoring, nonparametric and semiparametric hazard regression, multivariate survival data analysis, the sub-distribution method for competing risks data, the cure rate model, and Bayesian inference methods. The authors then focus on time-dependent diagnostic medicine and high-dimensional genetic data analysis. Many of the methods are illustrated with clinical examples. Emphasizing the applications of survival analysis techniques in genetics, this book presents a statistical framework for burgeoning research in this area and offers a set of established approaches for statistical analysis. It reveals a new way of looking at how predictors are associated with censored survival time and extracts novel statistical genetic methods for censored survival time outcome from the vast amount of research results in genomics.

Modelling Multivariate Interval Censored And Left Truncated Survival Data Using Proportional Hazards Model

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Author :
language : en
Publisher:
Release Date : 2004

Modelling Multivariate Interval Censored And Left Truncated Survival Data Using Proportional Hazards Model written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.

(Uncorrected OCR) Abstract of the thesis entitled MODELLING MULTIVARIATE INTERVAL-CENSORED AND LEFT-TRUNCATED SURVIVAL DATA USING PROPORTIONAL HAZARDS MODEL submitted by CHEUNG Tak Lun Alan for the degree of Master of Philosophy at The University of Hong Kong in December 2003 One of the main objectives in survival analysis is to investigate the effects of some potential explanatory variables on the survival times. One popular model used in such analysis is the celebrated Cox semiparametric proportional hazards model. Cox (1975) considered the partial likelihood, which only uses the rank of the uncensored survival times, to estimate regression parameter. However, the rank of the failure times is not available in the presence of interval censoring because it is too expensive or even impossible to monitor the experimental subjects continuously in most controlled clinical trials. To model interval-censored data with covariates, a simple multiple imputation approach is proposed to estimate the regression parameter of the Cox model. The basic idea is to iterate between the following two steps. With an additional Weibull assumption on the baseline hazard function, we first impute an exact failure time to each finite interval-censored time using the approximate conditional posterior distribution. Secondly, the standard Cox partial likelihood is applied to the imputed data and the estimate of the regression parameter is updated. The two steps are performed iteratively until convergence is achieved. Robust variance estimator for the regression parameter is also suggested to address the misspecification of the baseline hazard function. Although a parametric Weibull basline hazard function is specified, simulation studies show that the proposed method performs extremely well even when the baseline hazard function is piecewise constant. Applications to real life examples are provided. Practically, we cannot assume that the survival times of distinct individuals are independent t.

Dynamic Regression Models For Survival Data

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Author : Torben Martinussen
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-24

Dynamic Regression Models For Survival Data written by Torben Martinussen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-24 with Medical categories.

This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.

Lifetime Data Models In Reliability And Survival Analysis

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Author : Nicholas P. Jewell
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Lifetime Data Models In Reliability And Survival Analysis written by Nicholas P. Jewell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.

Statistical models and methods for lifetime and other time-to-event data are widely used in many fields, including medicine, the environmental sciences, actuarial science, engineering, economics, management, and the social sciences. For example, closely related statistical methods have been applied to the study of the incubation period of diseases such as AIDS, the remission time of cancers, life tables, the time-to-failure of engineering systems, employment duration, and the length of marriages. This volume contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University. The conference brought together a varied group of researchers and practitioners to advance and promote statistical science in the many fields that deal with lifetime and other time-to-event-data. The volume illustrates the depth and diversity of the field. A few of the authors have published their conference presentations in the new journal Lifetime Data Analysis (Kluwer Academic Publishers).

Modeling Survival Data Using Frailty Models

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Author : David D. Hanagal
language : en
Publisher: Springer Nature
Release Date : 2019-11-16

Modeling Survival Data Using Frailty Models written by David D. Hanagal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-16 with Medical categories.

This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.

Modelling Survival Data In Medical Research

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Author : David Collett
language : en
Publisher: CRC Press
Release Date : 2015-05-04

Modelling Survival Data In Medical Research written by David Collett and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-04 with Mathematics categories.

Modelling Survival Data in Medical Research describes the modelling approach to the analysis of survival data using a wide range of examples from biomedical research.Well known for its nontechnical style, this third edition contains new chapters on frailty models and their applications, competing risks, non-proportional hazards, and dependent censo