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The Impact Of Deviations From The Proportional Hazards Assumption On Power In The Analysis Of Survival Data
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Book Synopsis The Impact of Deviations from the Proportional Hazards Assumption on Power in the Analysis of Survival Data by : Todd Edward Gray
Download or read book The Impact of Deviations from the Proportional Hazards Assumption on Power in the Analysis of Survival Data written by Todd Edward Gray and published by . This book was released on 1996 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Clinical Trials in Oncology, Third Edition by : Stephanie Green
Download or read book Clinical Trials in Oncology, Third Edition written by Stephanie Green and published by CRC Press. This book was released on 2012-05-09 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.
Book Synopsis The Impact of the Violation of the Proportional Hazards Assumption on Confirmatory Analysis of Survival Data Using Delayed Entry by : Minkyu Kim
Download or read book The Impact of the Violation of the Proportional Hazards Assumption on Confirmatory Analysis of Survival Data Using Delayed Entry written by Minkyu Kim and published by . This book was released on 2015 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many clinical trials with staggered entry, interim analyses are conducted for monitoring purposes. If some unexpected results are found during the interim analyses, performing confirmatory analyses may be desirable. However, a completely new study with different patients in different locations requires a lot of additional resources such as time and money. Furthermore, there may be ethical concerns regarding recruitment of patients for a new study if a harmful treatment effect was found in a previous study. In this situation, the result illustrated in Keiding et al. (1987) may be helpful. It suggests use of recurrence-free survivors among the initial cohort as delayed entry when performing confirmatory analyses. Therefore, we can increase the sample size and power of confirmatory analyses by combining recurrence-free survivors with patients enrolled who have not contributed to the interim analyses. The result from Keiding et al. (1987) requires several assumptions but, our study focuses on the proportional hazards assumption. In simulations the validity of the proportional hazards assumption depends on the way we generate the datasets and the models we fit. We simulate two binary covariates, Treatment and Status: one indicating either the treatment group or the control group and the other indicating whether patients developed their disease a long or short time before enrollment. Patients who have had their disease for a long time are called “Early patients” because, in our simulations, we assume that they are enrolled during the earlier part of hypothetical studies. Patients who developed the disease shortly before enrollment are called “Late patients” because we assume that they are enrolled during the later part of the hypothetical studies. Therefore, there are four types of patients, early patients in either the treatment or the control group, and late patients in either the treatment or the control group. We use an interaction effect between the two factors and a change in patient mix (Early and Late patients) over time to create a time dependent treatment effect in a model that does not account for the interaction effect. We focus on investigating the power of confirmatory analyses that follow an interim anal- ysis which detected a significant harmful effect. We compare the power of confirmatory analyses that only use participants enrolled after the interim analysis to the power of con- firmatory analyses that use participants enrolled after the interim analysis combined with recurrence-free survivors from the initial cohort. For recurrence-free survivors only the time of observation after the interim analysis is used and it is used as delayed entry. We fit three models: (1) a model that includes only a treatment effect, (2) a model that includes a treatment effect and a status effect and (3) a model that includes a treatment effect, a status effect and an interaction effect. The likelihood ratio test with one-degree of freedom is performed to test for the treatment effect in (1) and (2) and the likelihood ratio test with two degrees of freedom (main and interaction effect) is performed to test for a treatment effect in (3). For each of these three models we ensure (separately) that the model has a significant treatment effect at the interim analysis. We choose time frames of enrollment and follow-up and sample sizes that are similar to the setting of Keiding et al. (1987). We use exponentially distributed hazard functions for each of the four patient groups. For each of the three models, the treatment effect is estimated using four different analysis cohorts: (i) the initial cohort prior to the interim analysis only, (ii) the cohort that does not contribute to the interim analysis (only), (iii) the cohort that does not contribute to the interim analysis combined with recurrence-free survivors but each contributing only up to one year of data, (iv) the latter, but contributing up to four years of data. For models 1 and 2, the power for the confirmatory analysis that uses the recurrence-free survivors can be higher, about the same or lower than the power of the analysis that does not use them depending on the strength of the interaction effect. The use of recurrence-free survivors can typically not overcome issues of fitting an incorrect model. In contrast, when fitting model 3, the power of the analysis that includes the recurrence-free survivors is always higher than the power of the analysis not using the recurrence-free survivors regardless of the size of the interaction effect and the treatment effect. As expected, in simulations where the proportional hazards assumption holds (either because there is no time trend or the time trend is included in the model) using recurrence- free survivors as delayed entry always improves power regardless of the size of the treatment and interaction effect.
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 Competing Risks and Multistate Models with R by : Jan Beyersmann
Download or read book Competing Risks and Multistate Models with R written by Jan Beyersmann and published by Springer Science & Business Media. This book was released on 2011-11-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.
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. This book was released on 2010-12-21 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing Survival Analysis and Event History Analysis is an accessible, practical and comprehensive guide for researchers and students 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 and resources for both students and instructors, Introducing Survival Analysis and Event History Analysis allows researchers to quickly master these advanced statistical techniques. This book is written from the perspective of the ′user′, making it suitable as both a self-learning tool and graduate-level textbook. Introducing Survival Analysis and Event History Analysis covers the most up-to-date innovations in the field, including advancements in the assessment of model fit, frailty and recurrent event models, discrete-time methods, competing and multistate models and sequence analysis. Practical instructions are also included, focusing on the statistical program R and Stata, enabling readers to replicate the examples described in the text. This book comes with a glossary, a range of practical and user-friendly examples, cases and exercises.
Book Synopsis The Frailty Model by : Luc Duchateau
Download or read book The Frailty Model written by Luc Duchateau and published by Springer Science & Business Media. This book was released on 2007-10-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readers will find in the pages of this book a treatment of the statistical analysis of clustered survival data. Such data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. A typical example is the time to death in cancer patients, with patients clustered in hospitals. Frailty models provide a powerful tool to analyze clustered survival data. In this book different methods based on the frailty model are described and it is demonstrated how they can be used to analyze clustered survival data. All programs used for these examples are available on the Springer website.
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 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 2000-08-11 with total page 372 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 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 Analysis of Failure and Survival Data by : Peter J. Smith
Download or read book Analysis of Failure and Survival Data written by Peter J. Smith and published by CRC Press. This book was released on 2017-07-28 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analysis of Failure and Survival Data is an essential textbook for graduate-level students of survival analysis and reliability and a valuable reference for practitioners. It focuses on the many techniques that appear in popular software packages, including plotting product-limit survival curves, hazard plots, and probability plots in the context of censored data. The author integrates S-Plus and Minitab output throughout the text, along with a variety of real data sets so readers can see how the theory and methods are applied. He also incorporates exercises in each chapter that provide valuable problem-solving experience. In addition to all of this, the book also brings to light the most recent linear regression techniques. Most importantly, it includes a definitive account of the Buckley-James method for censored linear regression, found to be the best performing method when a Cox proportional hazards method is not appropriate. Applying the theories of survival analysis and reliability requires more background and experience than students typically receive at the undergraduate level. Mastering the contents of this book will help prepare students to begin performing research in survival analysis and reliability and provide seasoned practitioners with a deeper understanding of the field.
Book Synopsis Proportional Hazards Regression by : John O'Quigley
Download or read book Proportional Hazards Regression written by John O'Quigley and published by Springer Science & Business Media. This book was released on 2008-01-25 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The place in survival analysis now occupied by proportional hazards models and their generalizations is so large that it is no longer conceivable to offer a course on the subject without devoting at least half of the content to this topic alone. This book focuses on the theory and applications of a very broad class of models – proportional hazards and non-proportional hazards models, the former being viewed as a special case of the latter – which underlie modern survival analysis. Researchers and students alike will find that this text differs from most recent works in that it is mostly concerned with methodological issues rather than the analysis itself.
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 Survival Analysis: State of the Art by : John P. Klein
Download or read book Survival Analysis: State of the Art written by John P. Klein and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Survival analysis is a highly active area of research with applications spanning the physical, engineering, biological, and social sciences. In addition to statisticians and biostatisticians, researchers in this area include epidemiologists, reliability engineers, demographers and economists. The economists survival analysis by the name of duration analysis and the analysis of transition data. We attempted to bring together leading researchers, with a common interest in developing methodology in survival analysis, at the NATO Advanced Research Workshop. The research works collected in this volume are based on the presentations at the Workshop. Analysis of survival experiments is complicated by issues of censoring, where only partial observation of an individual's life length is available and left truncation, where individuals enter the study group if their life lengths exceed a given threshold time. Application of the theory of counting processes to survival analysis, as developed by the Scandinavian School, has allowed for substantial advances in the procedures for analyzing such experiments. The increased use of computer intensive solutions to inference problems in survival analysis~ in both the classical and Bayesian settings, is also evident throughout the volume. Several areas of research have received special attention in the volume.
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.
Author :David G. Kleinbaum Publisher :Springer Science & Business Media ISBN 13 :9780387239187 Total Pages :616 pages Book Rating :4.2/5 (391 download)
Book Synopsis Survival Analysis by : David G. Kleinbaum
Download or read book Survival Analysis written by David G. Kleinbaum and published by Springer Science & Business Media. This book was released on 2005 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on survival analysis provides a straightforward and easy-to-follow introduction to the main concepts and techniques of the subject. It is based on numerous courses given by the author to students and researchers in the health sciences and is written with such readers in mind. Throughout, there is an emphasis on presenting each new topic motivated with real examples of a survival analysis investigation, and then presenting thorough analyses of real data sets. Each chapter concludes with practice exercises to help readers reinforce their understanding of the concepts covered in the chapter.
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.
