Survival Models and Data Analysis

ISBN-13: 9780471031741 / Angielski / Twarda / 1980 / 480 str.

Regina C. Elandt-Johnson;Elandt Johnson Regina C; Dis Norman Lloyd Johnson

Opis

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.

Spis treści

SURVIVAL MEASUREMENTS AND CONCEPTS.

Survival Data.

Measures of Mortality and Morbidity. Ratios, Proportions, and Means.

Survival Distributions.

MORTALITY EXPERIENCES AND LIFE TABLES.

Life Tables: Fundamentals and Construction.

Complete Mortality Data. Estimation of Survival Function.

Incomplete Mortality Data: Follow–Up Studies.

Fitting Parametric Survival Distributions.

Comparison of Mortality Experiences.

MULTIPLE TYPES OF FAILURE.

Theory of Competing Causes: Probabilistic Approach.

Multiple Decrement Life Tables.

Single Decrement Life Tables Associated with Multiple Decrement Life Tables: Their Interpretation and Meaning.

Estimation and Testing Hypotheses in Competing Risk Analysis.

SOME MORE ADVANCED TOPICS.

Concomitant Variables in Lifetime Distributions Models.

Age of Onset Distributions.

Models of Aging and Chronic Diseases.

Indexes.

O autorze

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.

Blurb

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