Philadelphia: SAGE, 2014. — 48 p. Social scientists are interested in events and their causes. Although event histories are ideal for studying the causes of events, they typically possess two features―censoring and time-varying explanatory variables―that create major problems for standard statistical procedures. Several innovative approaches have been developed to accommodate...
Cary: SAS Publishing, 2010. — 336 p. — ISBN: 1599946408, 9781599946405. Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new...
Boca Raton: CRC Press, 2023. — 293 p. Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more...
Faye Anderson, 2016. — 42 p. This is an applied handbook on survival analysis (also known as reliability or duration analysis) with annotated examples using S-Plus or R. This is the first book ever explaining survival analysis by example and is intended for users at all levels. The examples can easily be replicated using other software. Key topics include exploratory analyses,...
Basel: Birkhäuser, 2014. — 652 p. This monograph offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth in recent years. Progressive censoring, originally proposed in the 1950s, is an efficient method of handling samples from industrial experiments involving lifetimes of units that have either...
Elsevier, 2004. — 789 p. — (Handbook of Statistics 23). The book covers all important topics in the area of Survival Analysis. Each topic has been covered by one or more chapters written by internationally renowned experts. Each chapter provides a comprehensive and up-to-date review of the topic. Several new illustrative examples have been used to demonstrate the methodologies...
Amsterdam: North Holland, 2004. - 789p.
The book covers all important topics in the area of Survival Analysis. Each topic has been covered by one or more chapters written by internationally renowned experts. Each chapter provides a comprehensive and up-to-date review of the topic. Several new illustrative examples have been used to demonstrate the methodologies developed. The...
CRC Press, 2018. — 616 p. — (Chapman & Hall/CRC Interdisciplinary Statistics). — ISBN: 1420077473, 9781420077476. Survival Analysis with Interval-Censored Data: A Practical Approach with Examples in R, SAS, and BUGS provides the reader with a practical introduction into the analysis of interval-censored survival times. Although many theoretical developments have appeared in the...
New York: ISTE, 2017. — 196 p. This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature, the regression methods actually employed in...
New York: Stata Press, 2010. — 441 p.
An Introduction to Survival Analysis Using Stata, Third Edition provides the foundation to understand various approaches for analyzing time-to-event data. It is not only a tutorial for learning survival analysis but also a valuable reference for using Stata to analyze survival data. Although the book assumes knowledge of statistical...
Boca Raton: CEC Press, 1988. — 417 p. Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified formats for estimates, graphical techniques, and numerous tables and charts allowing users to calculate estimates and analyze sample data quickly and easily. Furnishing numerous practical examples, this...
Wiley-ISTE, 2013. — 251 p. Statistical Models and Methods for Reliability and Survival Analysis brings together contributions by specialists in statistical theory as they discuss their applications providing up-to-date developments in methods used in survival analysis, statistical goodness of fit, stochastic processes for system reliability, amongst others. Many of these are...
Boca Raton: CRC Press, 2018. — 212 p. 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...
Chapman and Hall/CRC, 2012. — 417 p. — ISBN: 1439875219, 9781439875216
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty...
New York: Chapman & Hall/CRC, 2019. — 493 p. Incidence rates are counts divided by person-time; mortality rates are a well-known example. Analysis of Incidence Rates offers a detailed discussion of the practical aspects of analyzing incidence rates. Important pitfalls and areas of controversy are discussed. The text is aimed at graduate students, researchers, and analysts in the...
Singapore: World Scientific, 2005. — 258 p. — ISBN: 981-256-607-4 This book is meant for postgraduate modules that cover lifetime data in reliability and survival analysis as taught in statistics, engineering statistics and medical statistics courses. It is helpful for researchers who wish to choose appropriate models and methods for analyzing lifetime data. There is an...
Singapore: Springer, 2018. — 94 p. This book introduces readers to copula-based statistical methods for analyzing survival data involving dependent censoring. Primarily focusing on likelihood-based methods performed under copula models, it is the first book solely devoted to the problem of dependent censoring. The book demonstrates the advantages of the copula-based methods in...
Singapore: Springer, 2019. — 126 p. This book introduces readers to advanced statistical methods for analyzing survival data involving correlated endpoints. In particular, it describes statistical methods for applying Cox regression to two correlated endpoints by accounting for dependence between the endpoints with the aid of copulas. The practical advantages of employing...
New York: Wiley, 2005. — 452 p. The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians,...
New York: Springer, 2019. — 307 p. 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...
2nd ed. — Wiley-Interscience, 2008. — 412 р. — ISBN: 0471754994, 9780471754992. The most practical, up-to-date guide to modelling and analyzing time-to-event data—now in a valuable new edition. Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of...
N.-Y.: Springer, 2001. — 493 p. — ISBN: 978-1-4419-2933-4.
Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. It presents a balance between theory and applications, and for each class of models discussed, detailed...
Springer, 2001. — 493 p. — ISBN: 978-1-4419-2933-4. Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. Several topics are addressed, including parametric models, semiparametric models based on prior processes,...
New York: Springer, 1996. — 392 p. 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...
Chapman and Hall/CRC, 2024. — 401 p. Many conventional survival analysis methods, such as the Kaplan-Meier method for survival function estimation and the partial likelihood method for Cox model regression coefficients estimation, were developed under the assumption that survival times are subject to right censoring only. However, in practice, survival time observations may...
N.-Y.: Springer, 2015. — 110 p.
Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expansions, allowing the replacement of linear effects by more general functions. The MCMC methodology for these models is presented in a unified...
2 ed. — Wiley, 2002. – 462 p. Book contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns, introduces the martingale and counting process formulations will be in a new chapter, develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov...
Springer, 2019. — 259 p. — ISBN: 978-981-13-9775-2. This book presents and standardizes statistical models and methods that can be directly applied to both reliability and survival analysis. These two types of analysis are widely used in many fields, including engineering, management, medicine, actuarial science, the environmental sciences, and the life sciences. Though there...
Springer, 2019. — 259 p. — ISBN: 978-981-13-9775-2. This book presents and standardizes statistical models and methods that can be directly applied to both reliability and survival analysis. These two types of analysis are widely used in many fields, including engineering, management, medicine, actuarial science, the environmental sciences, and the life sciences. Though there...
Second Edition. — N.-Y.: Springer, 2003. — 538 p. — ISBN: 0-387-95399-X.
Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on applications of the techniques to...
N.-Y.: Chapman and Hall/CRC, 2013. — 656 p. — ISBN: 978-1-4665-5567-9.
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,...
Third Edition. — Springer Science+Business Media, 2012. — 716 p. ISBN: 978-1441966452, e-ISBN: 978-1441966469. 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. Based on numerous courses given by the author to students and researchers in the health...
Springer Science+Business Media, Inc, 2005. - 596 p. - ISBN: 0387239189, 9780387953991. Applied statisticians in many fields frequently analyze time-to-event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics and demography, the focus here is on applications of the...
3rd Edition. — John Wiley & Sons, 2003. — 534 pages. — ISBN: 0471369977.
Third Edition brings the text up to date with new material and updated references.
New content includes an introduction to left and interval censored data; the log-logistic distribution; estimation procedures for left and interval censored data; parametric methods with covariates; Cox's proportional...
Boca Raton: CRC Press, 2021. — 361 p. Survival data analysis is a very broad field of statistics, encompassing a large variety of methods used in a wide range of applications, and in particular in medical research. During the last twenty years, several extensions of "classical" survival models have been developed to address particular situations often encountered in practice....
Singapore: Springer, 2022. — 367 p. Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and...
Wiley, 2014. — 464 p. — ISBN: 0470977159 Survival analysis concerns sequential occurrences of events governed by probabilistic laws. Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of...
Winsted: ACTEX Publications, 1997. — 384 p. It has been nearly ten years since the publication of the second edition of Survival Models and Their Estimation, and its adoption by the Society of Actuaries as the principal references for its Course 160 examination. It appears that the text has proved satisfactory in that role from the point of view of exam candidate and examiner...
Second Edition. — N.-Y.: Wiley, 2006. — 267 p. — ISBN: 978-0-470-87040-2.
Well received in its first edition, Survival Analysis: A Practical Approach is completely revised to provide an accessible and practical guide to survival analysis techniques in diverse environments. Illustrated with many authentic examples, the book introduces basic statistical concepts and methods to...
Hoboken: Wiley, 1997. — 154 p. The aim of this book is to suggest and exemplify a systematic methodology for analysing survival data which contains "immune", or "cured" individuals, denoted generically as "long-term survivors". Such data occurs in medical and epidemiological applications, where the intention may be to identify whether or not cured or immune individuals are...
Hoboken: Wiley–Blackwell, 1975. — 584 p. Elements of Probability Theory Elements of Statistical Theory Statistical Failure Models Point and Interval Estimation Procedures for Lifetime Distributions (Failure Models) Testing Reliability Hypotheses Goodness of Fit, Monte Carlo, and Distribution-Free Methods Bayes Methods in Reliability Accelerated Life Testing and Related Topics...
New York: Springer, 2007. — 783 p. — (Springer Series in Statistics). — ISBN: 978-0-387-20333-1. For over 200 years, practitioners have been developing parametric families of probability distributions for data analysis. More recently, an active development of nonparametric and semiparametric families has occurred. This book includes an extensive discussion of a wide variety of...
Springer, 2009. — 450 p. In survival analysis there has long been a need for models that goes beyond the Cox model as the proportional hazards assumption often fails in practice. 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 specific aim of describing...
New York: Springer, 2016. — 218 p. — (Use R!) — ISBN: 331931243X. Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical...
New York: Springer, 2016. — 234 p. — (Use R!) Applied Survival Analysis Using R covers the main principles of survival analysis, gives examples of how it is applied, and teaches how to put those principles to use to analyze data using R as a vehicle. Survival data, where the primary outcome is time to a specific event, arise in many areas of biomedical research, including clinical...
CRC Press, 2022. — 94 p. — ISBN: 978-1-032-07367-5. Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis As the subject itself is very mathematical and full of expressions and formulations, the book...
CRC Press, 2022. — 94 p. — ISBN: 978-1-032-07367-5. Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis As the subject itself is very mathematical and full of expressions and formulations, the book...
New York: Springer, 2016. - 131p.
This book will be of interest to readers active in the fields of survival analysis, genetics, ecology, biology, demography, reliability and quality control.
Since Sir David Cox’s pioneering work in 1972, the proportional hazards model has become the most important model in survival analysis. The success of the Cox model stimulated further...
Springer, 2021. — 476 p. — ISBN 978-3-030-33438-3. 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...
Springer, 2021. — 476 p. — ISBN 978-3-030-33438-3. 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...
Boca Raton: CRC Press, 2002. — 267 p. Contains the most up-to-date advances in the field, including the definitive account of the Buckley-James method for censored data Uses the S-PLUS software for data analysis and incorporates output throughout the text Includes many worked examples and a range of both theoretical and applied problems in each chapter Emphasizes the importance...
New York: Chapman and Hall/CRC, 2001. — 260 p. Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some fundamental concepts be rethought and suitably redefined....
Springer, 2006. — 302 p. Survival analysis, the analysis of failure time data, is a rapid developing area and a number of books on the topic have been published in last twenty-five years. However, all of these books deal with right-censored failure time data, not the analysis of interval-censored failure time data. Interval-censored data include right-censored data as a special...
Chapman and Hall/CRC, 2004. — 277 p. — ISBN: 0-203-50141-1, 0-203-59444-4. 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...
New York: Chapman and Hall/CRC, 2022. — 303 p. Survival analysis generally deals with analysis of data arising from clinical trials. Censoring, truncation, and missing data create analytical challenges and the statistical methods and inference require novel and different approaches for analysis. Statistical properties, essentially asymptotic ones, of the estimators and tests...
Boca Raton: CRC Press, 2016. - 257 p.
Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book is a three-state process for dementia and...
Chapman and Hall/CRC, 2010. — 312 p. — ISBN: 1420073885.
The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival...
N.Y.: CRC Press, 2015. — 220 p. Empirical Likelihood Method in Survival Analysis explains how to use the empirical likelihood method for right censored survival data. The author uses R for calculating empirical likelihood and includes many worked out examples with the associated R code. The datasets and code are available for download on his website and CRAN. The book focuses on...
Wiesbaden: Springer Spektrum, 2017. — 103 p. Mathematically Rigorous Treatment of Basic Survival Analytic Methods Georg Zimmermann provides a mathematically rigorous treatment of basic survival analytic methods. His emphasis is also placed on various questions and problems, especially with regard to life expectancy calculations arising from a particular real-life dataset on...
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