survival models and data analysis wiley series in probability and statistics

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Survival Models And Data Analysis

Author : Regina C. Elandt-Johnson
ISBN : 9781119011033
Genre : Mathematics
File Size : 37. 27 MB
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Survival analysis deals with the distribution of life times, essentially the times from an initiating event such as birth or the start of a job to some terminal event such as death or pension. This book, originally published in 1980, surveys and analyzes methods that use survival measurements and concepts, and helps readers apply the appropriate method for a given situation. Four broad sections cover introductions to data, univariate survival function, multiple-failure data, and advanced topics.

Statistical Methods For Survival Data Analysis

Author : Elisa T. Lee
ISBN : 0471615927
Genre : Mathematics
File Size : 85. 65 MB
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Intended to meet the requirements for a single volume which covers methodologies appropriate for the analysis of survival data. Along with guidelines for the planning and design of clinical trials this expanded Second Edition offers a thorough discussion of population lifetables, real life examples, numerous exercises, computer programs for survival data analysis plus an updated reference list which includes a large number of recently published papers.

Statistical Methods For Survival Data Analysis

Author : Elisa T. Lee
ISBN : UOM:39015056677324
Genre : Mathematics
File Size : 84. 83 MB
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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 iwth covariates; Cox's proportional hazards model (including stratification and time-dependent covariates); and multiple responses to the logistic regression model. Coverage of graphical methods has been deleted. Large data sets are provided on an FTP site for readers' convenience. Bibliographic remarks conclude each chapter.

Applied Survival Analysis

Author : David W. Hosmer, Jr.
ISBN : STANFORD:36105025984183
Genre : Mathematics
File Size : 48. 87 MB
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A Practical, Up-To-Date Guide To Modern Methods In The Analysis Of Time To Event Data. The rapid proliferation of powerful and affordable statistical software packages over the past decade has inspired the development of an array of valuable new methods for analyzing survival time data. Yet there continues to be a paucity of statistical modeling guides geared to the concerns of health-related researchers who study time to event data. This book helps bridge this important gap in the literature. Applied Survival Analysis is a comprehensive introduction to regression modeling for time to event data used in epidemiological, biostatistical, and other health-related research. Unlike other texts on the subject, it focuses almost exclusively on practical applications rather than mathematical theory and offers clear, accessible presentations of modern modeling techniques supplemented with real-world examples and case studies. While the authors emphasize the proportional hazards model, descriptive methods and parametric models are also considered in some detail. Key topics covered in depth include: * Variable selection. * Identification of the scale of continuous covariates. * The role of interactions in the model. * Interpretation of a fitted model. * Assessment of fit and model assumptions. * Regression diagnostics. * Recurrent event models, frailty models, and additive models. * Commercially available statistical software and getting the most out of it. Applied Survival Analysis is an ideal introduction for graduate students in biostatistics and epidemiology, as well as researchers in health-related fields.

Applied Survival Analysis

Author : David W. Hosmer, Jr.
ISBN : 9781118211588
Genre : Mathematics
File Size : 45. 10 MB
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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 model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.

Statistical Models And Methods For Lifetime Data

Author : Jerald F. Lawless
ISBN : 9781118031254
Genre : Mathematics
File Size : 26. 23 MB
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Praise for the First Edition "An indispensable addition to any serious collection on lifetimedata analysis and . . . a valuable contribution to the statisticalliterature. Highly recommended . . ." -Choice "This is an important book, which will appeal to statisticiansworking on survival analysis problems." -Biometrics "A thorough, unified treatment of statistical models and methodsused in the analysis of lifetime data . . . this is a highlycompetent and agreeable statistical textbook." -Statistics in Medicine The statistical analysis of lifetime or response time data is a keytool in engineering, medicine, and many other scientific andtechnological areas. This book provides a unified treatment of themodels and statistical methods used to analyze lifetime data. Equally useful as a reference for individuals interested in theanalysis of lifetime data and as a text for advanced students,Statistical Models and Methods for Lifetime Data, Second Editionprovides broad coverage of the area without concentrating on anysingle field of application. Extensive illustrations and examplesdrawn from engineering and the biomedical sciences provide readerswith a clear understanding of key concepts. New and expanded coverage in this edition includes: * Observation schemes for lifetime data * Multiple failure modes * Counting process-martingale tools * Both special lifetime data and general optimizationsoftware * Mixture models * Treatment of interval-censored and truncated data * Multivariate lifetimes and event history models * Resampling and simulation methodology

Game Theory Optimal Stopping Probability And Statistics

Author : F. Thomas Bruss
ISBN : 094060048X
Genre : Mathematics
File Size : 54. 39 MB
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Survival Analysis

Author : Rupert G. Miller, Jr.
ISBN : 9781118031063
Genre : Mathematics
File Size : 79. 61 MB
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A concise summary of the statistical methods used in the analysis of survival data with censoring. Emphasizes recently developed nonparametric techniques. Outlines methods in detail and illustrates them with actual data. Discusses the theory behind each method. Includes numerous worked problems and numerical exercises.

The Statistical Analysis Of Failure Time Data

Author : J. D. Kalbfleisch
ISBN : 0471055190
Genre : Mathematics
File Size : 23. 6 MB
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Synthesizes statistical models and methods for the analysis of failure time or ''survival'' data. Focuses on regression problems with survival data, specifically the estimation of regression coefficients and distributional shape in the presence of shaping. Deals with the theory, applications and extensions of the proportional hazards model. Includes worked examples and problems for solution.

Survival Analysis

Author : Xian Liu
ISBN : 9781118307670
Genre : Mathematics
File Size : 67. 33 MB
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Survival analysis concerns sequential occurrences of eventsgoverned by probabilistic laws. Recent decades have witnessedmany applications of survival analysis in various disciplines. Thisbook introduces both classic survival models and theories alongwith newly developed techniques. Readers will learn how to performanalysis of survival data by following numerous empiricalillustrations in SAS. Survival Analysis: Models andApplications: Presents basic techniques before leading onto some of the mostadvanced topics in survival analysis. Assumes only a minimal knowledge of SAS whilst enabling moreexperienced users to learn new techniques of data inputand manipulation. Provides numerous examples of SAS code to illustrate each ofthe methods, along with step-by-step instructions to perform eachtechnique. Highlights the strengths and limitations of each techniquecovered. Covering a wide scope of survival techniques and methods, fromthe introductory to the advanced, this book can be used as a usefulreference book for planners, researchers, and professors who areworking in settings involving various lifetime events. Scientists interested in survival analysis should find it a usefulguidebook for the incorporation of survival data and methods intotheir projects.

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