Hybrid Censoring: Models, Methods and Applications
for Engineering and Bio Health
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.
Life science and engineering scientists and researchers who need to analyze censored or truncated life time data and students, researchers and practitioners in different areas such as statistics, industrial engineering and clinical trials.