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Survival analysis (Biometry) --- Censored observations (Statistics) --- Biochemistry
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Survival analysis (Biometry) --- Censored observations (Statistics) --- Biochemistry
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During the last decades, there has been an explosion in computation and information technology. This development comes with an expansion of complex observational studies and clinical trials in a variety of fields such as medicine, biology, epidemiology, sociology, and economics among many others, which involve collection of large amounts of data on subjects or organisms over time. The goal of such studies can be formulated as estimation of a finite dimensional parameter of the population distribution corresponding to the observed time-dependent process. Such estimation problems arise in survival analysis, causal inference and regression analysis. This book provides a fundamental statistical framework for the analysis of complex longitudinal data. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures subject to informative censoring and treatment assignment in so called semiparametric models. Semiparametric models are particularly attractive since they allow the presence of large unmodeled nuisance parameters. These techniques include estimation of regression parameters in the familiar (multivariate) generalized linear regression and multiplicative intensity models. They go beyond standard statistical approaches by incorporating all the observed data to allow for informative censoring, to obtain maximal efficiency, and by developing estimators of causal effects. It can be used to teach masters and Ph.D. students in biostatistics and statistics and is suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.
Nonparametric statistics --- Longitudinal method --- Estimation theory --- Statistique non-paramétrique --- Méthode longitudinale --- Théorie de l'estimation --- Censored observations (Statistics) --- Estimation theory. --- Longitudinal method. --- Nonparametric statistics. --- Censored observations (Statistics).
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Biometry --- Demography --- Multi-State Information System --- Censored observations (Statistics) --- Stochastic processes
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Elasticity. --- Flexure --- Strength of materials --- Censored observations (Statistics) --- Wood --- Weibull distribution. --- Mathematical models. --- Mechanical properties --- Elastic properties
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Censored observations (Statistics) --- Nonparametric statistics --- Distribution (Probability theory) --- Survival analysis (Biometry) --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Congresses --- Congresses --- Congresses
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Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers will find information on the significance of censored data in theoretical and applied contexts, and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography.
Censored observations (Statistics) --- Engineering --- Statistical methods. --- Engineering statistics --- Engineering mathematics --- Censored data (Statistics) --- Censoring (Statistics) --- Mathematical statistics --- Biomedical engineering --- Statistics as Topic --- Models, Statistical
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