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 : 78. 61 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 : 71. 4 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.

Game Theory Optimal Stopping Probability And Statistics

Author : F. Thomas Bruss
ISBN : 094060048X
Genre : Mathematics
File Size : 65. 36 MB
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Statistical Methods For Survival Data Analysis

Author : Elisa T. Lee
ISBN : UOM:39015056677324
Genre : Mathematics
File Size : 52. 23 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.

Statistical Models And Methods For Lifetime Data

Author : Jerald F. Lawless
ISBN : 9781118031254
Genre : Mathematics
File Size : 51. 33 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

Applied Survival Analysis

Author : David W. Hosmer, Jr.
ISBN : 9781118211588
Genre : Mathematics
File Size : 53. 89 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.

Introduction To Statistical Time Series

Author : Wayne A. Fuller
ISBN : 9780470317754
Genre : Mathematics
File Size : 80. 32 MB
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The subject of time series is of considerable interest, especially among researchers in econometrics, engineering, and the natural sciences. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new Second Edition, covers the important advances of recent years, including nonstationary models, nonlinear estimation, multivariate models, state space representations, and empirical model identification. New sections have also been added on the Wold decomposition, partial autocorrelation, long memory processes, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material, especially on elementary results in Fourier analysis, large sample statistics, and difference equations, has been included.

Nonparametric Statistical Methods

Author : Myles Hollander
ISBN : 9781118553299
Genre : Mathematics
File Size : 55. 3 MB
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Praise for the Second Edition “This book should be an essential part of the personallibrary of every practicingstatistician.”—Technometrics Thoroughly revised and updated, the new edition of NonparametricStatistical Methods includes additional modern topics andprocedures, more practical data sets, and new problems fromreal-life situations. The book continues to emphasize theimportance of nonparametric methods as a significant branch ofmodern statistics and equips readers with the conceptual andtechnical skills necessary to select and apply the appropriateprocedures for any given situation. Written by leading statisticians, Nonparametric StatisticalMethods, Third Edition provides readers with crucialnonparametric techniques in a variety of settings, emphasizing theassumptions underlying the methods. The book provides an extensivearray of examples that clearly illustrate how to use nonparametricapproaches for handling one- or two-sample location and dispersionproblems, dichotomous data, and one-way and two-way layoutproblems. In addition, the Third Edition features: The use of the freely available R software to aid incomputation and simulation, including many new R programs writtenexplicitly for this new edition New chapters that address density estimation, wavelets,smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science,astronomy, biology, criminology, education, engineering,environmental science, geology, home economics, medicine,oceanography, physics, psychology, sociology, and spacescience Nonparametric Statistical Methods, Third Edition is anexcellent reference for applied statisticians and practitioners whoseek a review of nonparametric methods and their relevantapplications. The book is also an ideal textbook forupper-undergraduate and first-year graduate courses in appliednonparametric statistics.

Precedence Type Tests And Applications

Author : N. Balakrishnan
ISBN : 9780470037836
Genre : Mathematics
File Size : 45. 24 MB
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Periodically Correlated Random Sequences

Author : Harry L. Hurd
ISBN : 0470182822
Genre : Mathematics
File Size : 23. 35 MB
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Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures. Features of the book include: An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum A balanced blend of historical background with modern application-specific references to periodically correlated processes An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB® for performing time series analysis on data that may have a PC structure Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory.

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