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Author: Robert Elashoff
Publisher: CRC Press
ISBN: 1439807833
Category : Mathematics
Languages : en
Pages : 262
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Book Description
Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.
Author: Claude Romano
Publisher: Perspectives in Continental Ph
ISBN: 9780823255344
Category : Philosophy
Languages : en
Pages : 269
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Book Description
The book critically analyzes the subjectivization of time in traditional metaphysics (Plato, Aristotle, Augustine), as well as more recent thought (Bergson, Husserl, Heidegger), and argues that, instead, the guiding thread for the analysis of time ought to be the evential hermeneutics of the human being, developed first in Event and World and deepened and completed here.
Author: Robert Elashoff
Publisher: CRC Press
ISBN: 1439807833
Category : Mathematics
Languages : en
Pages : 262
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Book Description
Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables, informative observation times of longitudinal data, and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data, as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.
Author: Aparna V. Huzurbazar
Publisher: John Wiley & Sons
ISBN: 0471686530
Category : Mathematics
Languages : en
Pages : 320
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Book Description
A unique introduction to the innovative methodology of statisticalflowgraphs This book offers a practical, application-based approach toflowgraph models for time-to-event data. It clearly shows how thisinnovative new methodology can be used to analyze data fromsemi-Markov processes without prior knowledge of stochasticprocesses--opening the door to interesting applications in survivalanalysis and reliability as well as stochastic processes. Unlike other books on multistate time-to-event data, this workemphasizes reliability and not just biostatistics, illustratingeach method with medical and engineering examples. It demonstrateshow flowgraphs bring together applied probability techniques andcombine them with data analysis and statistical methods to answerquestions of practical interest. Bayesian methods of data analysisare emphasized. Coverage includes: * Clear instructions on how to model multistate time-to-event datausing flowgraph models * An emphasis on computation, real data, and Bayesian methods forproblem solving * Real-world examples for analyzing data from stochasticprocesses * The use of flowgraph models to analyze complex stochasticnetworks * Exercise sets to reinforce the practical approach of thisvolume Flowgraph Models for Multistate Time-to-Event Data is an invaluableresource/reference for researchers in biostatistics/survivalanalysis, systems engineering, and in fields that use stochasticprocesses, including anthropology, biology, psychology, computerscience, and engineering.
Author: Dimitris Rizopoulos
Publisher: CRC Press
ISBN: 1439872864
Category : Mathematics
Languages : en
Pages : 279
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Book Description
In longitudinal studies it is often of interest to investigate how a marker that is repeatedly measured in time is associated with a time to an event of interest, e.g., prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R provides a full treatment of random effects joint models for longitudinal and time-to-event outcomes that can be utilized to analyze such data. The content is primarily explanatory, focusing on applications of joint modeling, but sufficient mathematical details are provided to facilitate understanding of the key features of these models. All illustrations put forward can be implemented in the R programming language via the freely available package JM written by the author. All the R code used in the book is available at: http://jmr.r-forge.r-project.org/
Author: Karl E. Peace
Publisher: CRC Press
ISBN: 1420066404
Category : Mathematics
Languages : en
Pages : 618
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Book Description
Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "noninformativeness" of the censoring mechanisms relative to the event. Design and Analysis of Clinical Trials with Time-to-Event Endpoints provides a thorough presentation o
Author: Hongsheng Dai
Publisher: Academic Press
ISBN: 0081010087
Category : Mathematics
Languages : en
Pages : 104
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Book Description
Survival Analysis for Bivariate Truncated Data provides readers with a comprehensive review on the existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function. The most distinguishing feature of survival data is known as censoring, which occurs when the survival time can only be exactly observed within certain time intervals. A second feature is truncation, which is often deliberate and usually due to selection bias in the study design. Truncation presents itself in different ways. For example, left truncation, which is often due to a so-called late entry bias, occurs when individuals enter a study at a certain age and are followed from this delayed entry time. Right truncation arises when only individuals who experienced the event of interest before a certain time point can be observed. Analyzing truncated survival data without considering the potential selection bias may lead to seriously biased estimates of the time to event of interest and the impact of risk factors. - Assists statisticians, epidemiologists, medical researchers, and actuaries who need to understand the mechanism of selection bias - Reviews existing works on survival analysis for truncated data, mainly focusing on the estimation of univariate and bivariate survival function - Offers a guideline for analyzing truncated survival data
Author: Basem El-Haik
Publisher: John Wiley & Sons
ISBN: 0470047712
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
This is the first book to completely cover the whole body of knowledge of Six Sigma and Design for Six Sigma with Simulation Methods as outlined by the American Society for Quality. Both simulation and contemporary Six Sigma methods are explained in detail with practical examples that help understanding of the key features of the design methods. The systems approach to designing products and services as well as problem solving is integrated into the methods discussed.
Author: Ding-Geng (Din) Chen
Publisher: CRC Press
ISBN: 1466504250
Category : Mathematics
Languages : en
Pages : 435
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Book Description
Interval-Censored Time-to-Event Data: Methods and Applications collects the most recent techniques, models, and computational tools for interval-censored time-to-event data. Top biostatisticians from academia, biopharmaceutical industries, and government agencies discuss how these advances are impacting clinical trials and biomedical research. Divided into three parts, the book begins with an overview of interval-censored data modeling, including nonparametric estimation, survival functions, regression analysis, multivariate data analysis, competing risks analysis, and other models for interval-censored data. The next part presents interval-censored methods for current status data, Bayesian semiparametric regression analysis of interval-censored data with monotone splines, Bayesian inferential models for interval-censored data, an estimator for identifying causal effect of treatment, and consistent variance estimation for interval-censored data. In the final part, the contributors use Monte Carlo simulation to assess biases in progression-free survival analysis as well as correct bias in interval-censored time-to-event applications. They also present adaptive decision making methods to optimize the rapid treatment of stroke, explore practical issues in using weighted logrank tests, and describe how to use two R packages. A practical guide for biomedical researchers, clinicians, biostatisticians, and graduate students in biostatistics, this volume covers the latest developments in the analysis and modeling of interval-censored time-to-event data. It shows how up-to-date statistical methods are used in biopharmaceutical and public health applications.
Author: Teerawat Issariyakul
Publisher: Springer Science & Business Media
ISBN: 0387717609
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
An Introduction to Network Simulator NS2 is a beginners’ guide for network simulator NS2, an open-source discrete event simulator designed mainly for networking research. NS2 has been widely accepted as a reliable simulation tool for computer communication networks both in academia and industry. This book will present two fundamental NS2 concepts:i) how objects (e.g., nodes, links, queues, etc.) are assembled to create a network and ii) how a packet flows from one object to another. Based on these concepts, this book will demonstrate through examples how new modules can be incorporated into NS2. The book will: -Give an overview on simulation and communication networks. -Provide general information (e.g., installation, key features, etc.) about NS2. -Demonstrate how to set up a simple network simulation scenario using Tcl scripting lanuage. -Explain how C++ and OTcl (Object oriented Tcl) are linked, and constitute NS2. -Show how Ns2 interprets a Tcl Script and executes it. -Suggest post simulation processing approaches and identify their pros and cons. -Present a number of NS2 extension examples. -Discuss how to incorporate MATLAB into NS2.
Author: G. BIRTWISTLE
Publisher: Springer
ISBN: 1489966854
Category : Computers
Languages : en
Pages : 225
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Book Description
