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Inhaltsangabe
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.
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Über die Autorin bzw. den Autor
About the authors REGINA C. ELANDT-JOHNSON has been Professor of Biostatistics at the University of North Carolina at Chapel Hill since 1964. She is the author of Probability Models and Statistical Methods in Genetics (Wiley, 1971). Dr. Elandt-Johnson received her Ph.D. in statistics from Poznan Agricultural University in 1957. NORMAN L. JOHNSON is Alumni Distinguished Professor at the University of North Carolina at Chapel Hill. Dr. Johnson served as Chairman of the Fisher Memorial Lecture Committee, American Statistical Association from 1976 until 1979. He is co-author of Distributions in Statistics (Wiley, 1969-1972); URN Models and their Applications (Wiley, 1977); and Statistics and Experimental Design in Engineering and Physical Sciences (Wiley, 1977). Dr. Johnson received his D.Sc. in statistics from University College, London in 1963.
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This book describes methods of analyzing survival data and construction of interpretative models. The authors guide the reader in the use of the literature, assist in the choice of appropriate methods, and warn against uncritical use. Emphasis is on the ideas behind the methods and interpretation of results. Numerical examples from diverse fields are worked out in considerable detail. Part I introduces the type of data to be analyzed and basic concepts useful in analysis. Part II deals with problems that relate to univariate survival functions. It includes construction of life tables from population (cross sectional) data and experimental follow-up data. Methods are mostly nonparametric, though fitting parametric distributions and comparisons of two or more mortality experiences are discussed. Part III concerns multiple failure data, identifying time and cause of death. This section treats parametric and nonparametric theories of competing causes, and estimation of different kinds of failure distributions. Part IV presents selected, advanced topics, including speculative mathematical models of disease progression and survival. These are intended to suggest some of the ways models may be constructed. Survival Models and Data Analysis is a guide for biostatisticians, statisticians, mathematicians, biologists, biomedical personnel, sociologists, and students. Mathematics are employed when in the interests of clarification and consistency; thus, a knowledge of algebra and introductory calculus is presupposed.
Aus dem Klappentext
This book describes methods of analyzing survival data and construction of interpretative models. The authors guide the reader in the use of the literature, assist in the choice of appropriate methods, and warn against uncritical use. Emphasis is on the ideas behind the methods and interpretation of results. Numerical examples from diverse fields are worked out in considerable detail. Part I introduces the type of data to be analyzed and basic concepts useful in analysis. Part II deals with problems that relate to univariate survival functions. It includes construction of life tables from population (cross sectional) data and experimental follow-up data. Methods are mostly nonparametric, though fitting parametric distributions and comparisons of two or more mortality experiences are discussed. Part III concerns multiple failure data, identifying time and cause of death. This section treats parametric and nonparametric theories of competing causes, and estimation of different kinds of failure distributions. Part IV presents selected, advanced topics, including speculative mathematical models of disease progression and survival. These are intended to suggest some of the ways models may be constructed. Survival Models and Data Analysis is a guide for biostatisticians, statisticians, mathematicians, biologists, biomedical personnel, sociologists, and students. Mathematics are employed when in the interests of clarification and consistency; thus, a knowledge of algebra and introductory calculus is presupposed.
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- VerlagWiley-Interscience
- Erscheinungsdatum1980
- ISBN 10 0471031747
- ISBN 13 9780471031741
- EinbandTapa dura
- SpracheEnglisch
- Auflage1
- Anzahl der Seiten484
- Kontakt zum HerstellerNicht verfügbar
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Survival Models and Data Analysis (Wiley Series in Probability and Mathematical Statistics)
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Survival Models and Data Analysis (Wiley Series in Probability and Mathematical Statistics)
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Zustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. No dust jacket. Library sticker on front cover. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:0471031747. Artikel-Nr. 9292990
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Survival Models and Data Analysis
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Wiley & Sons, Incorporated, John, 1980
ISBN 10: 0471031747
ISBN 13: 9780471031741
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Survival Models and Data Analysis
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Zustand: New. Über den AutorAbout the authors REGINA C. ELANDT-JOHNSON has been Professor of Biostatistics at the University of North Carolina at Chapel Hill since 1964. She is the author of Probability Models and Statistical Methods in Genetics . Artikel-Nr. 446914284
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Buch. Zustand: Neu. Neuware - Other volumes in the Wiley Series in Probability and Mathematical Statistics: Ralph A. Bradley, J. Stuart Hunter, David G. Kendall, and Geoffrey S. Watson-- Advisory Editors The Statistical Analysis of Failure Time Data John D. Kalbfleisch & Ross L. Prentice This volume collects and unifies statistical models proposed for the analysis of failure time data in the biomedical, industrial, and engineering sciences. The focus is on regression problems with survival data, specifically estimation of regression coefficients and distributional shape in the presence of censoring. Contains specific biographical notes, historical summaries, theoretical and applied problems, numerous worked examples, and computer programs. 1980 Biostatistics Casebook Edited by Rupert G. Miller, Jr., Bradley Efron, Byron Wm. Brown, Jr., and Lincoln E. Moses This book deals with the statistical aspects of actual biomedical research problems. It provides enough of the scientific background of each problem to guide the statistical approach. Using the case study method, the book discusses many new and specially developed concepts and techniques, often applying a variety of techniques to the same detailed data set. 1980 Survival Distributions: Reliability Applications in the Biomedical Sciences Alan J. Gross & Virginia A. Clark 'This book is clearly arranged [and] can be recommended to students and to those who want to become acquainted with the techniques for analysing life test data from the practical standpoint.'--Technometrics Describes nonparametric and parametric techniques used to achieve more reliable survival distributions in biomedical applications. Introduces commonly used survival distributions and covers applications of clinical life tables. Includes mathematical and graphical techniques for accurately selecting appropriate survival distributions to fit survival data, models for analyzing growth in reliability for clinical trials and industrial applications, a complete methodology for comparing two treatment groups when length of survival is the comparison criterion, and new help for choosing, in advance of clinical trial, the number of patients required for an adequate sample. 1975. Artikel-Nr. 9780471031741
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