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Author: Odd Aalen Publisher: Springer Science & Business Media ISBN: 038768560X Category : Mathematics Languages : en Pages : 550
Book Description
The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics.
Author: Odd Aalen Publisher: Springer Science & Business Media ISBN: 038768560X Category : Mathematics Languages : en Pages : 550
Book Description
The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully. The common denominator of such models is stochastic processes. The authors show how counting processes, martingales, and stochastic integrals fit very nicely with censored data. Beginning with standard analyses such as Kaplan-Meier plots and Cox regression, the presentation progresses to the additive hazard model and recurrent event data. Stochastic processes are also used as natural models for individual frailty; they allow sensible interpretations of a number of surprising artifacts seen in population data. The stochastic process framework is naturally connected to causality. The authors show how dynamic path analyses can incorporate many modern causality ideas in a framework that takes the time aspect seriously. To make the material accessible to the reader, a large number of practical examples, mainly from medicine, are developed in detail. Stochastic processes are introduced in an intuitive and non-technical manner. The book is aimed at investigators who use event history methods and want a better understanding of the statistical concepts. It is suitable as a textbook for graduate courses in statistics and biostatistics.
Author: Melinda Mills Publisher: SAGE ISBN: 1848601026 Category : Social Science Languages : en Pages : 301
Book Description
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.
Author: Paul David Allison Publisher: SAGE ISBN: 9780803920552 Category : Social Science Languages : en Pages : 92
Book Description
Drawing on recent "event history" analytical methods from biostatistics, engineering, and sociology, this clear and comprehensive monograph explains how longitudinal data can be used to study the causes of deaths, crimes, wars, and many other human events. Allison shows why ordinary multiple regression is not suited to analyze event history data, and demonstrates how innovative regression - like methods can overcome this problem. He then discusses the particular new methods that social scientists should find useful.
Author: Göran Broström Publisher: CRC Press ISBN: 1315360527 Category : Mathematics Languages : en Pages : 238
Book Description
With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional hazards, and accelerated failure times. Features Introduces parametric proportional hazards models with baseline distributions like the Weibull, Gompertz, Lognormal, and Piecewise constant hazard distributions, in addition to traditional Cox regression Presents mathematical details as well as technical material in an appendix Includes real examples with applications in demography, econometrics, and epidemiology Provides a dedicated R package, eha, containing special treatments, including making cuts in the Lexis diagram, creating communal covariates, and creating period statistics A much-needed primer, Event History Analysis with R is a didactically excellent resource for students and practitioners of applied event history and survival analysis.
Author: Hans-Peter Blossfeld Publisher: Psychology Press ISBN: 131778572X Category : Psychology Languages : en Pages : 298
Book Description
Serving as both a student textbook and a professional reference/handbook, this volume explores the statistical methods of examining time intervals between successive state transitions or events. Examples include: survival rates of patients in medical studies, unemployment periods in economic studies, or the period of time it takes a criminal to break the law after his release in a criminological study. The authors illustrate the entire research path required in the application of event-history analysis, from the initial problems of recording event-oriented data to the specific questions of data organization, to the concrete application of available program packages and the interpretation of the obtained results. Event History Analysis: * makes didactically accessible the inclusion of covariates in semi-parametric and parametric regression models based upon concrete examples * presents the unabbreviated close relationship underlying statistical theory * details parameter-free methods of analysis of event-history data and the possibilities of their graphical presentation * discusses specific problems of multi-state and multi-episode models * introduces time-varying covariates and the question of unobserved population heterogeneity * demonstrates, through examples, how to implement hypotheses tests and how to choose the right model.
Author: Hans-Peter Blossfeld Publisher: Psychology Press ISBN: 1135595933 Category : Business & Economics Languages : en Pages : 313
Book Description
Event History Analysis With Stata provides an introduction to event history modeling techniques using Stata (version 9), a widely used statistical program that provides tools for data analysis. The book emphasizes the usefulness of event history models for causal analysis in the social sciences and the application of continuous-time models. T
Author: Hans-Peter Blossfeld Publisher: Routledge ISBN: 0429522541 Category : Psychology Languages : en Pages : 352
Book Description
Nowadays, event history analysis can draw on a well-established set of statistical tools for the description and causal analysis of event history data. The second edition of Event History Analysis with Stata provides an updated introduction to event history modeling, along with many instructive Stata examples. Using the latest Stata software, each of these practical examples develops a research question, refers to useful substantive background information, gives a short exposition of the underlying statistical concepts, describes the organization of the input data and the application of the statistical Stata procedures, and assists the reader in performing a substantive interpretation of the obtained results. Emphasising the strengths and limitations of event history model techniques in each field of application, this book demonstrates that event history models provide a useful approach with which to uncover causal relationships or to map out a system of causal relations. It demonstrates how long-term processes can be studied and how changing context information on the micro, meso, and macro levels can be integrated easily into a dynamic analysis of longitudinal data. Event History Analysis with Stata is an invaluable resource for both novice students and researchers who need an introductory textbook and experienced researchers (from sociology, economics, political science, pedagogy, psychology, or demography) who are looking for a practical handbook for their research.
Author: Mario Cleves Publisher: Stata Press ISBN: 1597180416 Category : Computers Languages : en Pages : 398
Book Description
"[This book] provides new researchers with the foundation for understanding the various approaches for analyzing time-to-event data. This book serves not only as a tutorial for those wishing to learn survival analysis but as a ... reference for experienced researchers ..."--Book jacket.
Author: Mara Tableman Publisher: CRC Press ISBN: 0203501411 Category : Mathematics Languages : en Pages : 277
Book Description
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.
Author: Odd Aalen
Author: Odd Aalen
Author: Melinda Mills
Author: Paul David Allison
Author: Göran Broström
Author: Janet M. Box-Steffensmeier
Author: Hans-Peter Blossfeld
Author: Hans-Peter Blossfeld
Author: Hans-Peter Blossfeld
Author: Mario Cleves
Author: Mara Tableman