Survival Models and Data Analysis / Edition 1

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Overview

A detailed survey of methods which utilize data from population censuses and other demographic sources, actuarial records, and clinical trials. Analyzes similarities and differences between the various methods, providing criteria for determining methodological suitability for particular problems.
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Editorial Reviews

Booknews
Combines material and techniques developed in several different disciplines, such as epidemiology, reliability theory, and statistical methods, on what with a slight shift of emphasis could be called mortality data, as they appear in a myriad of contexts from small-scale laboratory tests to massive records of long-term clinical trials. Sets out general principles of the various models and includes exercises that can be worked out different ways in order to discourage people from mistaking any particular method for exclusive truth. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

Meet the Author

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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Table of Contents

Pt. 1 Survival Measurements and Concepts
1 Survival Data 3
2 Measures of mortality and morbidity, ratios, proportions, and means 9
3 Survival distributions 50
Pt. 2 Mortality Experiences and Life Tables
4 Life tables: fundamentals and construction 83
5 Complete mortality data. estimation of survival function 128
6 Incomplete mortality data: follow-up studies 150
7 Fitting parametric survival distributions 181
8 Comparison of mortality experiences 225
Pt. 3 Multiple Types of Failure
9 Theory of competing causes: probabilistic approach 269
10 Multiple decrement life tables 294
11 Single decrement life tables associated with multiple decrement life tables: their interpretation and meaning 309
12 Estimation and testing hypotheses in competing risk analysis 323
Pt. 4 Some More Advanced Topics
13 Concomitant variables in lifetime distributions models 345
14 Age of onset distributions 392
15 Models of aging and chronic diseases 414
Author index 433
Subject index 447
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