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9780123983879 English 0123983878 " Hybrid Censoring: Models, Methods and Applications for Engineering and Bio Health" focuses on hybrid censoring, a specific yet important topic in censoring methodology that has numerous applications. 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, or 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 by providing readers with valuable information on these topics. The statistical tools presented are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all the inferential methods discussedProvides open problems and possible directions for future workReviews developments pertaining to Type-II HCS, and includes the most recent research and trendsExplains why the hybrid censored sampling is importantProvides detail in using HCS under different settings and the designs of HCSIncludes R code on website for ease of use, "Hybrid Censoring: Models, Methods and Applications: " For Engineering and Bio Health focuses on hybrid censoring, a specific, but important topic in censoring methodology that has numerous applications. 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. As existing literature on censoring methodology, life-testing procedures, or lifetime data analysis provide only hybrid censoring schemes and little information on the methodologies, ideas, and statistical inferential methods for hybrid censoring, this book fills that gap, giving readers valuable information on these topics. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all the inferential methods discussedProvides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS, and includes the most recent research and trends. Explains why the hybrid censored sampling is importantProvides detail in using HCS under different settings and the designs of HCSIncludes R code on website for ease of use, Hybrid Censoring: Models, Methods and Applications focuses on hybrid censoring, a specific but important topic in censoring methodology, which has numerous applications. Applied statisticians in many fields must frequently analyze time-to-event data. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. This work explains the significance of censored data in theoretical and applied contexts. It describes extensive data sets from life-testing experiments where these forms of data occur naturally. The existing literature on censoring methodology, life-testing procedures or lifetime data analysis provide only some hybrid censoring schemes but do not spend a significant amount of time to detail the methodologies, ideas and statistical inferential methods for hybrid censoring. This book fills this gap and provides valuable information on these topics. Presents many numerical examples to adequately illustrate all the inferential methods discussed Provides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS and includes the most recent research and trends Explains why the hybrid censored sampling is important, provides detail in using HCS under different settings and the designs of HCS Includes R code on website for ease of use, This book focuses on hybrid censoring, a specific but important topic in censoring methodology, which has numerous applications. Applied statisticians in many fields must frequently analyze time to event data. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. This work presents why the analysis of censored data is important from an applied point of view as well as from a theoretical point of view. Extensive data sets from life-testing experiments where these forms of data occur naturally are described. The analysis of survival experiments is complicated by issues of censoring, in which an individual's life length is known to occur only in a certain period, and by truncation, in which individuals enter the study only if they survive a sufficient time or if individuals are included in the study only if the event has occurred by a given date. The existing literature on censoring methodology, life-testing procedures or lifetime data analysis provide only some hybrid censoring schemes but do not spend a significant amount of time to detail the methodologies, ideas and statistical inferential methods for hybrid censoring. This book fills this gap and provides valuable information on these topics. Presents many numerical examples to adequately illustrate all the inferential methods discussed Provides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS and includes the most recent research and trends Explains why the hybrid censored sampling is important, provides detail in using HCS under different settings and the designs of HCS Includes R code on website for ease of use
9780123983879 English 0123983878 " Hybrid Censoring: Models, Methods and Applications for Engineering and Bio Health" focuses on hybrid censoring, a specific yet important topic in censoring methodology that has numerous applications. 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, or 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 by providing readers with valuable information on these topics. The statistical tools presented are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all the inferential methods discussedProvides open problems and possible directions for future workReviews developments pertaining to Type-II HCS, and includes the most recent research and trendsExplains why the hybrid censored sampling is importantProvides detail in using HCS under different settings and the designs of HCSIncludes R code on website for ease of use, "Hybrid Censoring: Models, Methods and Applications: " For Engineering and Bio Health focuses on hybrid censoring, a specific, but important topic in censoring methodology that has numerous applications. 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. As existing literature on censoring methodology, life-testing procedures, or lifetime data analysis provide only hybrid censoring schemes and little information on the methodologies, ideas, and statistical inferential methods for hybrid censoring, this book fills that gap, giving readers valuable information on these topics. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all the inferential methods discussedProvides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS, and includes the most recent research and trends. Explains why the hybrid censored sampling is importantProvides detail in using HCS under different settings and the designs of HCSIncludes R code on website for ease of use, Hybrid Censoring: Models, Methods and Applications focuses on hybrid censoring, a specific but important topic in censoring methodology, which has numerous applications. Applied statisticians in many fields must frequently analyze time-to-event data. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. This work explains the significance of censored data in theoretical and applied contexts. It describes extensive data sets from life-testing experiments where these forms of data occur naturally. The existing literature on censoring methodology, life-testing procedures or lifetime data analysis provide only some hybrid censoring schemes but do not spend a significant amount of time to detail the methodologies, ideas and statistical inferential methods for hybrid censoring. This book fills this gap and provides valuable information on these topics. Presents many numerical examples to adequately illustrate all the inferential methods discussed Provides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS and includes the most recent research and trends Explains why the hybrid censored sampling is important, provides detail in using HCS under different settings and the designs of HCS Includes R code on website for ease of use, This book focuses on hybrid censoring, a specific but important topic in censoring methodology, which has numerous applications. Applied statisticians in many fields must frequently analyze time to event data. The statistical tools presented within are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. This work presents why the analysis of censored data is important from an applied point of view as well as from a theoretical point of view. Extensive data sets from life-testing experiments where these forms of data occur naturally are described. The analysis of survival experiments is complicated by issues of censoring, in which an individual's life length is known to occur only in a certain period, and by truncation, in which individuals enter the study only if they survive a sufficient time or if individuals are included in the study only if the event has occurred by a given date. The existing literature on censoring methodology, life-testing procedures or lifetime data analysis provide only some hybrid censoring schemes but do not spend a significant amount of time to detail the methodologies, ideas and statistical inferential methods for hybrid censoring. This book fills this gap and provides valuable information on these topics. Presents many numerical examples to adequately illustrate all the inferential methods discussed Provides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS and includes the most recent research and trends Explains why the hybrid censored sampling is important, provides detail in using HCS under different settings and the designs of HCS Includes R code on website for ease of use