"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 discussedProvides open problems and possible
directions for future work Reviews developments pertaining to
Type-II HCS and includes the most recent research and
trendsExplains 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
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