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Survival Analysis With Internal Categorical Time Varying Covariates
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Book Synopsis Survival Analysis with Internal Categorical Time-varying Covariates by : Charles D.G. Keown-Stoneman
Download or read book Survival Analysis with Internal Categorical Time-varying Covariates written by Charles D.G. Keown-Stoneman and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the study of time-to-event data, an important feature is the ability to include time-varying covariates. Concerns have been raised over the use of Cox models in the presence of internal time-varying covariates. Multi-state models have been proposed as an acceptable alternative approach for internal time-varying covariates. A motivating example throughout this thesis is the development of bipolar disorder. It has been proposed that bipolar disorder progresses in a predictable sequence of clinical stages. In Chapter 2 the objective is to compare Cox models and non-parametric multi-state models in the presence of other psychiatric diagnoses. These diagnoses are coded as binary time-varying covariates in a Cox model or as states in a non-parametric multi-state model. A common assumption in Cox models with time-varying covariates is that the effect of a covariate on the event of interest is constant and permanent after it has changed. Chapter 3 presents a modification to the usual Cox model for binary time-varying covariates that allows the influence of a covariate to exponentially decay over time. Methods for generating data using the inverse cumulative density function for the proposed model are developed. Likelihood ratio tests and AIC are investigated as methods for comparing the proposed model with the commonly used permanent exposure model. A simulation study is performed and three different example data analyses are presented. One advantage to parametric multi-state models is the inclusion of misclassification. Until now, this approach has largely been confined to exponential waiting times within each state. In Chapter 4 we introduce Bayesian parametric multi-state models with unknown misclassification of states and Weibull distributed waiting times between states. Weibull waiting times allow transitions between states to depend on the time spent in the current state, a feature lacking in exponential waiting times. To fit the proposed Bayesian model, a Markov chain Monte Carlo (MCMC) Metropolis-Hastings algorithm is employed. The motivating example on the progression of bipolar disorder is presented along with simulation results. From the example analysis, there is evidence that assuming Weibull waiting times is an improvement over assuming exponential waiting times in the study of bipolar disorder.
Download or read book Survival Analysis written by Shenyang Guo and published by Oxford University Press. This book was released on 2010-01-25 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival analysis is a class of statistical methods for studying the occurrence and timing of events. With clearly written summaries and plentiful examples, this pocket guide will put this important statistical tool in the hands of many more social work researchers than have been able to use it before.
Book Synopsis Analysis of Survival Data by : D.R. Cox
Download or read book Analysis of Survival Data written by D.R. Cox and published by Routledge. This book was released on 2018-02-19 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.
Book Synopsis Introducing Survival and Event History Analysis by : Melinda Mills
Download or read book Introducing Survival and Event History Analysis written by Melinda Mills and published by SAGE Publications. This book was released on 2011-01-19 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an accessible, practical and comprehensive guide for researchers from multiple disciplines including biomedical, epidemiology, engineering and the social sciences. Written for accessibility, this book will appeal to students and researchers who want to understand the basics of survival and event history analysis and apply these methods without getting entangled in mathematical and theoretical technicalities. Inside, readers are offered a blueprint for their entire research project from data preparation to model selection and diagnostics. Engaging, easy to read, functional and packed with enlightening examples, ‘hands-on’ exercises, conversations with key scholars and resources for both students and instructors, this text allows researchers to quickly master advanced statistical techniques. It is written from the perspective of the ‘user’, making it suitable as both a self-learning tool and graduate-level textbook. Also included are up-to-date innovations in the field, including advancements in the assessment of model fit, unobserved heterogeneity, recurrent events and multilevel event history models. Practical instructions are also included for using the statistical programs of R, STATA and SPSS, enabling readers to replicate the examples described in the text.
Book Synopsis Handbook of Survival Analysis by : John P. Klein
Download or read book Handbook of Survival Analysis written by John P. Klein and published by CRC Press. This book was released on 2016-04-19 with total page 635 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Survival Analysis presents modern techniques and research problems in lifetime data analysis. This area of statistics deals with time-to-event data that is complicated by censoring and the dynamic nature of events occurring in time. With chapters written by leading researchers in the field, the handbook focuses on advances in survival analysis techniques, covering classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field. Accessible to a wide range of readers, the book provides: An introduction to various areas in survival analysis for graduate students and novices A reference to modern investigations into survival analysis for more established researchers A text or supplement for a second or advanced course in survival analysis A useful guide to statistical methods for analyzing survival data experiments for practicing statisticians
Book Synopsis Survival Analysis Using S by : Mara Tableman
Download or read book Survival Analysis Using S written by Mara Tableman and published by CRC Press. This book was released on 2003-07-28 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival Analysis Using S: Analysis of Time-to-Event Data is designed as a text for a one-semester or one-quarter course in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. Prerequisites are a standard pre-calculus first course in probability and statistics, and a course in applied linear regression models. No prior knowledge of S or R is assumed. A wide choice of exercises is included, some intended for more advanced students with a first course in mathematical statistics. The authors emphasize parametric log-linear models, while also detailing nonparametric procedures along with model building and data diagnostics. Medical and public health researchers will find the discussion of cut point analysis with bootstrap validation, competing risks and the cumulative incidence estimator, and the analysis of left-truncated and right-censored data invaluable. The bootstrap procedure checks robustness of cut point analysis and determines cut point(s). In a chapter written by Stephen Portnoy, censored regression quantiles - a new nonparametric regression methodology (2003) - is developed to identify important forms of population heterogeneity and to detect departures from traditional Cox models. By generalizing the Kaplan-Meier estimator to regression models for conditional quantiles, this methods provides a valuable complement to traditional Cox proportional hazards approaches.
Book Synopsis Survival Analysis by : Alejandro Quiroz Flores
Download or read book Survival Analysis written by Alejandro Quiroz Flores and published by Cambridge University Press. This book was released on 2022-05-26 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative social scientists use survival analysis to understand the forces that determine the duration of events. This Element provides a guideline to new techniques and models in survival analysis, particularly in three areas: non-proportional covariate effects, competing risks, and multi-state models. It also revisits models for repeated events. The Element promotes multi-state models as a unified framework for survival analysis and highlights the role of general transition probabilities as key quantities of interest that complement traditional hazard analysis. These quantities focus on the long term probabilities that units will occupy particular states conditional on their current state, and they are central in the design and implementation of policy interventions.
Book Synopsis Survival Analysis by : David G. Kleinbaum
Download or read book Survival Analysis written by David G. Kleinbaum and published by Springer. This book was released on 2006-01-02 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: An excellent introduction for all those coming to the subject for the first time. New material has been added to the second edition and the original six chapters have been modified. The previous edition sold 9500 copies world wide since its release in 1996. Based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Provides a "user-friendly" layout and includes numerous illustrations and exercises. Written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets.
Book Synopsis Dynamic Prediction in Clinical Survival Analysis by : Hans van Houwelingen
Download or read book Dynamic Prediction in Clinical Survival Analysis written by Hans van Houwelingen and published by CRC Press. This book was released on 2011-11-09 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime a
Book Synopsis Semiparametric Analysis of an Expanded Cox Proportional Hazards Model with Time-varying Covariates by : Wenying Zheng
Download or read book Semiparametric Analysis of an Expanded Cox Proportional Hazards Model with Time-varying Covariates written by Wenying Zheng and published by . This book was released on 2016 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time-varying covariates are often encountered in survival analysis. The Cox proportional hazards model can incorporate time-varying covariates, while the interpretation of regression parameters is less straightforward. We instead propose a complementary log-log survival model. When covariates are time-independent, the proposed model reduces to the Cox proportional hazards model; however, when they are time-varying, the proposed model provides a direct interpretation of regression parameters in the survival function. We develop semiparametric estimation procedures based on estimating equations, and establish the asymptotic properties of the estimators for the regression parameters and survival functions. In addition, we include weight functions to the estimating equations to improve efficiency. We demonstrate the proposed methods by simulation studies and application to the Mayo Clinic Primary Biliary Cirrhosis data and data from a landmark HIV randomized prevention trial.
Book Synopsis Modeling Survival Data: Extending the Cox Model by : Terry M. Therneau
Download or read book Modeling Survival Data: Extending the Cox Model written by Terry M. Therneau and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for statistical practitioners, particularly those who design and analyze studies for survival and event history data. Building on recent developments motivated by counting process and martingale theory, it shows the reader how to extend the Cox model to analyze multiple/correlated event data using marginal and random effects. The focus is on actual data examples, the analysis and interpretation of results, and computation. The book shows how these new methods can be implemented in SAS and S-Plus, including computer code, worked examples, and data sets.
Book Synopsis Analysis of Multivariate Survival Data by : Philip Hougaard
Download or read book Analysis of Multivariate Survival Data written by Philip Hougaard and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Survival Analysis by : David G. Kleinbaum
Download or read book Survival Analysis written by David G. Kleinbaum and published by Springer. This book was released on 2011-10-15 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: An excellent introduction for all those coming to the subject for the first time. New material has been added to the second edition and the original six chapters have been modified. The previous edition sold 9500 copies world wide since its release in 1996. Based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Provides a "user-friendly" layout and includes numerous illustrations and exercises. Written in such a way so as to enable readers learn directly without the assistance of a classroom instructor. Throughout, there is an emphasis on presenting each new topic backed by real examples of a survival analysis investigation, followed up with thorough analyses of real data sets.
Book Synopsis The Cumulative Effects of Time-Varying Covariates in Survival Analysis by : Matthew Lowe
Download or read book The Cumulative Effects of Time-Varying Covariates in Survival Analysis written by Matthew Lowe and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Joint models for survival are modern statistical techniques for modelling the effect of time-varying covariates measured with error on the hazard of survival. Previous research has demonstrated that joint models have less bias compared to traditional Cox models with time-varying covariates. This thesis compares three association structures for joint models: the current value specification, the cumulative specification, and the weighted cumulative specification. The three methods were compared on two real data sets. A simulation study compared the three specifications when fit to data generated according to the current value specification. Results from the simulation show that the current value and weighted cumulative specifications provide similar estimates, with small bias and accurate standard deviation.
Book Synopsis Modelling Survival Data in Medical Research, Second Edition by : David Collett
Download or read book Modelling Survival Data in Medical Research, Second Edition written by David Collett and published by CRC Press. This book was released on 2003-03-28 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail. Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices.
Book Synopsis Survival Analysis by : John P. Klein
Download or read book Survival Analysis written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.
Book Synopsis Survival Analysis with Time-dependent Covariates by : Jesse Irwin Frank
Download or read book Survival Analysis with Time-dependent Covariates written by Jesse Irwin Frank and published by . This book was released on 1977 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt:
