Censoring and Truncation Mechanisms

Md. Rezaul Karim () and M. Ataharul Islam ()
Additional contact information
Md. Rezaul Karim: University of Rajshahi, Department of Statistics
M. Ataharul Islam: University of Dhaka, Institute of Statistical Research and Training

Chapter Chapter 4 in Reliability and Survival Analysis, 2019, pp 57-70 from Springer

Abstract: Abstract Censoring and truncation are the special types of characteristics of time to event data. A censored observation arises when the value of the random variable of interest is not known exactly, that is, only partial information about the value is known. In the case of truncation, some of the subjects may be dropped from the study due to the implementation of some conditions such that their presence or existence cannot be known. In other words, the truncated subjects are subjects to screening by some conditions as an integral part of the study. This chapter presents the maximum likelihood estimation method for analyzing the censored and truncated data.

Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-13-9776-9_4

Ordering information: This item can be ordered from
http://www.springer.com/9789811397769

DOI: 10.1007/978-981-13-9776-9_4

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().