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Sinopsis
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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Acerca del 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.
De la contraportada
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.
De la solapa interior
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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- EditorialWiley-Interscience
- Año de publicación1980
- ISBN 10 0471031747
- ISBN 13 9780471031741
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de edición1
- Número de páginas484
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Survival Models and Data Analysis
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Wiley-Interscience, 1980
ISBN 10: 0471031747
ISBN 13: 9780471031741
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Survival Models and Data Analysis (Wiley Series in Probability and Mathematical Statistics)
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ISBN 13: 9780471031741
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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
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SURVIVAL MODELS AND DATA ANALYSIS
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Survival Models and Data Analysis (Wiley Series in Probability and Statistics)
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hardcover. Condición: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority! Nº de ref. del artículo: S_425803197
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Survival Models and Data Analysis (Wiley Series in Probability and Statistics)
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ISBN 13: 9780471031741
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