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.