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Mathematical statistics --- Failure time data analysis. --- Survival analysis (Biometry). --- Failure time data analysis --- Survival analysis (Biometry) --- 368.01 --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Analysis, Failure time data --- Data analysis, Failure time --- Biometry --- Failure analysis (Engineering) --- Competing risks

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Mathematical statistics --- Failure time data analysis --- Reliability (Engineering) --- Temps entre défaillances, Analyse des --- Fiabilité --- Survival analysis (Biometry) --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Failure time data analysis. --- Survival analysis (Biometry). --- Temps entre défaillances, Analyse des --- Fiabilité

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Failure time data analysis --- Regression analysis --- Survival analysis (Biometry) --- 519.23 --- 519.2 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Mathematical statistics --- Competing risks --- 519.2 Probability. Mathematical statistics --- Probability. Mathematical statistics --- 519.23 Statistical analysis. Inference methods --- Statistical analysis. Inference methods --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry

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Survival analysis, the analysis of failure time data, is a rapid developing area and a number of books on the topic have been published in last twenty-five years. However, all of these books deal with right-censored failure time data, not the analysis of interval-censored failure time data. Interval-censored data include right-censored data as a special case and occur in many fields. The analysis of interval-censored data is much more difficult than that of right-censored data because the censoring mechanism that yields interval censoring is more complicated than that for right censoring. This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. A number of inference approaches are discussed in the book, including the maximum likelihood, estimating equations, sieve maximum likelihood, and conditional likelihood. One major difference between the analyses of right- and interval-censored data is that the theory of counting processes, which is responsible for substantial advances in the theory and development of modern statistical methods for right-censored data, is not applicable to interval-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. In addition, Bayesian methods and the analysis of interval-censored data with informative interval censoring are considered as well as the analysis of interval-censored recurrent event, or panel count, data. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions. It can also be used as a text for a graduate course in statistics or biostatistics that assume a basic knowledge of probability and statistics. Jianguo (Tony) Sun is a professor at the Department of Statistics of the University of Missouri-Columbia. He has developed novel statistical methods for the analysis of interval-censored failure time data and panel count data over the last fifteen years.

Failure time data analysis. --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Mathematical statistics --- Competing risks --- Survival analysis (Biometry) --- Distribution (Probability theory. --- Statistics. --- Probability Theory and Stochastic Processes. --- Statistics for Life Sciences, Medicine, Health Sciences. --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Probabilities. --- Statistics . --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk

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* Contains additional discussion and examples on left truncation as well as material on more general censoring and truncation patterns. * Introduces the martingale and counting process formulation swil lbe in a new chapter. * Develops multivariate failure time data in a separate chapter and extends the material on Markov and semi Markov formulations. * Presents new examples and applications of data analysis.

Mathematical statistics --- QA 276 .K215 Mathematical statistics --- Failure time data analysis --- Survival analysis (Biometry) --- Regression analysis --- AA / International- internationaal --- 303.0 --- 304.0 --- 519.5 --- Analysis, Regression --- Linear regression --- Regression modeling --- Multivariate analysis --- Structural equation modeling --- Analysis, Survival (Biometry) --- Survivorship analysis (Biometry) --- Biometry --- Analysis, Failure time data --- Data analysis, Failure time --- Failure analysis (Engineering) --- Competing risks --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen. --- Failure time data analysis. --- Regression analysis. --- Survival analysis (Biometry). --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken) --- Zuivere statistische analyse (algemene naslagwerken). Tijdreeksen