Hybrid Censoring: Models, Methods and Applications

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