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Survival Analysis, O`Quigley


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Автор: O`Quigley
Название:  Survival Analysis
ISBN: 9783030334413
Издательство: Springer
Классификация:



ISBN-10: 3030334414
Обложка/Формат: Soft cover
Страницы: 475
Вес: 0.88 кг.
Дата издания: 12.05.2022
Язык: English
Издание: 1st ed. 2021
Иллюстрации: 13 illustrations, color; 47 illustrations, black and white; xvi, 475 p. 60 illus., 13 illus. in color.; 13 illustrations, color; 47 illustrations, bla
Размер: 154 x 234 x 29
Читательская аудитория: Postgraduate, research & scholarly
Основная тема: Mathematics
Подзаголовок: Proportional and Non-Proportional Hazards Regression
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book provides an extensive coverage of the methodology of survival analysis, ranging from introductory level material to deeper more advanced topics.


Applied survival analysis using r

Автор: Moore, Dirk F.
Название: Applied survival analysis using r
ISBN: 331931243X ISBN-13(EAN): 9783319312439
Издательство: Springer
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Цена: 6986.00 р.
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Описание: 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.

Lifetime Data: Models in Reliability and Survival Analysis

Автор: Nicholas P. Jewell; Alan C. Kimber; Mei-Ling Ting
Название: Lifetime Data: Models in Reliability and Survival Analysis
ISBN: 0792337832 ISBN-13(EAN): 9780792337836
Издательство: Springer
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Цена: 29209.00 р.
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Описание: Contains a selection of papers based on the 1994 International Research Conference on Lifetime Data Models in Reliability and Survival Analysis, held at Harvard University.

Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications

Автор: Jo?o Lita da Silva; Frederico Caeiro; Isabel Nat?r
Название: Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications
ISBN: 3642446299 ISBN-13(EAN): 9783642446290
Издательство: Springer
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Цена: 29209.00 р.
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Описание: This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009.

Statistical Methods for Survival Data Analysis, 4th Edition

Автор: Lee
Название: Statistical Methods for Survival Data Analysis, 4th Edition
ISBN: 1118095022 ISBN-13(EAN): 9781118095027
Издательство: Wiley
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Цена: 18050.00 р.
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Описание: Upgraded to reflect the latest research and software applications on the topic, this new edition continues to provide a comprehensive introduction to the statistical methods for analyzing survival data.

Analysis of failure and survival data

Автор: Smith, Peter J. (royal Melbourne Institute Of Technology, Australia)
Название: Analysis of failure and survival data
ISBN: 1584880759 ISBN-13(EAN): 9781584880752
Издательство: Taylor&Francis
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Цена: 14545.00 р.
Наличие на складе: Поставка под заказ.

Описание: Suitable for students of survival analysis and reliability, this textbook integrates the use of contemporary statistical software output throughout the text along with a variety of real data sets so readers can see how theories and techniques are applied. It also brings to light linear regression techniques.

Handbook of Survival Analysis

Автор: Klein, John P.
Название: Handbook of Survival Analysis
ISBN: 1466555661 ISBN-13(EAN): 9781466555662
Издательство: Taylor&Francis
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Цена: 29093.00 р.
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Survival Analysis

Автор: David G. Kleinbaum; Mitchel Klein
Название: Survival Analysis
ISBN: 1493950185 ISBN-13(EAN): 9781493950188
Издательство: Springer
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Цена: 11179.00 р.
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Описание:

This greatly expanded second edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. This text is suitable for researchers and statisticians working in the medical and other life sciences as well as statisticians in academia who teach introductory and second-level courses on survival analysis. The second edition continues to use the unique "lecture-book" format of the first (1996) edition with the addition of three new chapters on advanced topics:

Chapter 7: Parametric Models

Chapter 8: Recurrent events

Chapter 9: Competing Risks.

Also, the Computer Appendix has been revised to provide step-by-step instructions for using the computer packages STATA (Version 7.0), SAS (Version 8.2), and SPSS (version 11.5) to carry out the procedures presented in the main text.

The original six chapters have been modified slightly

to expand and clarify aspects of survival analysis in response to suggestions by students, colleagues and reviewers, and

to add theoretical background, particularly regarding the formulation of the (partial) likelihood functions for proportional hazards, stratified, and extended Cox regression models

David Kleinbaum is Professor of Epidemiology at the Rollins School of Public Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationally known for innovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has provided extensive worldwide short-course training in over 150 short courses on statistical and epidemiological methods. He is also the author of ActivEpi (2002), an interactive computer-based instructional text on fundamentals of epidemiology, which has been used in a variety of educational environments including distance learning.

Mitchel Klein is Research Assistant Professor with a joint appointment in the Department of Environmental and Occupational Health (EOH) and the Department of Epidemiology, also at the Rollins School of Public Health at Emory University. Dr. Klein is also co-author with Dr. Kleinbaum of the second edition of Logistic Regression- A Self-Learning Text (2002). He has regularly taught epidemiologic methods courses at Emory to graduate students in public health and in clinical medicine. He is responsible for the epidemiologic methods training of physicians enrolled in Emory's Master of Science in Clinical Research Program, and has collaborated with Dr. Kleinbaum both nationally and internationally in teaching several short courses on various topics in epidemiologic methods.

Empirical likelihood method in survival analysis

Автор: Zhou, Mai
Название: Empirical likelihood method in survival analysis
ISBN: 0367377578 ISBN-13(EAN): 9780367377571
Издательство: Taylor&Francis
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Цена: 9798.00 р.
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Описание:

Add the Empirical Likelihood to Your Nonparametric Toolbox



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 all the standard survival analysis topics treated with empirical likelihood, including hazard functions, cumulative distribution functions, analysis of the Cox model, and computation of empirical likelihood for censored data. It also covers semi-parametric accelerated failure time models, the optimality of confidence regions derived from empirical likelihood or plug-in empirical likelihood ratio tests, and several empirical likelihood confidence band results.





While survival analysis is a classic area of statistical study, the empirical likelihood methodology has only recently been developed. Until now, just one book was available on empirical likelihood and most statistical software did not include empirical likelihood procedures. Addressing this shortfall, this book provides the functions to calculate the empirical likelihood ratio in survival analysis as well as functions related to the empirical likelihood analysis of the Cox regression model and other hazard regression models.

Survival Analysis: State of the Art

Автор: John P. Klein; P.K. Goel
Название: Survival Analysis: State of the Art
ISBN: 0792316347 ISBN-13(EAN): 9780792316343
Издательство: Springer
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Цена: 38433.00 р.
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Описание: Topics considered in this collection of papers are the use of frailty models in survival analysis, left-censored and left-truncated data, multivariate survival analysis, competing risks theory, kernel density estimation and semiparametric estimation for right-censored data.

Survival analysis with python

Автор: Nag, Avishek
Название: Survival analysis with python
ISBN: 1032148268 ISBN-13(EAN): 9781032148267
Издательство: Taylor&Francis
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Цена: 8726.00 р.
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Описание: Survival analysis uses statistics to calculate time to failure. The book takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis.

Regression Modeling Strategies

Автор: Frank E. Harrell , Jr.
Название: Regression Modeling Strategies
ISBN: 331933039X ISBN-13(EAN): 9783319330396
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Most of the methods in this text apply to all regression models, but special emphasis is given to multiple regression using generalised least squares for longitudinal data, the binary logistic model, models for ordinal responses, parametric survival regression models and the Cox semi parametric survival model.

Regression Modeling Strategies

Автор: Frank E. Harrell
Название: Regression Modeling Strategies
ISBN: 1441929185 ISBN-13(EAN): 9781441929181
Издательство: Springer
Рейтинг:
Цена: 12571.00 р.
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Описание: There are many books that are excellent sources of knowledge about individual stastical tools (survival models, general linear models, etc.), but the art of data analysis is about choosing and using multiple tools. In the words of Chatfield ..".students typically know the technical details of regressin for example, but not necessarily when and how to apply it. This argues the need for a better balance in the literature and in statistical teaching between techniques and problem solving strategies." Whether analyzing risk factors, adjusting for biases in observational studies, or developing predictive models, there are common problems that few regression texts address. For example, there are missing data in the majority of datasets one is likely to encounter (other than those used in textbooks ) but most regression texts do not include methods for dealing with such data effectively, and texts on missing data do not cover regression modeling.


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