Bayesian statistical inference of loglogistic model with interval-censored lifetime data

The properties of Palm Oil (PO) and Coconut Oil (CO) offer the potential for transformers Interval-censored data arise when a failure time say, T cannot be observed directly but can only be determined to lie in an interval obtained from a series of inspection times. The frequentist approach for anal...

Full description

Bibliographic Details
Main Authors: Guure, Chris Bambey, Ibrahim, Noor Akma, Dwomoh, Duah, Bosomprah, Samuel
Format: Article
Language:English
Published: Taylor & Francis 2015
Online Access:http://psasir.upm.edu.my/id/eprint/43915/
http://psasir.upm.edu.my/id/eprint/43915/1/Bayesian%20statistical%20inference%20of%20the%20loglogistic%20model%20with%20interval-censored%20lifetime%20.pdf
_version_ 1848850357739847680
author Guure, Chris Bambey
Ibrahim, Noor Akma
Dwomoh, Duah
Bosomprah, Samuel
author_facet Guure, Chris Bambey
Ibrahim, Noor Akma
Dwomoh, Duah
Bosomprah, Samuel
author_sort Guure, Chris Bambey
building UPM Institutional Repository
collection Online Access
description The properties of Palm Oil (PO) and Coconut Oil (CO) offer the potential for transformers Interval-censored data arise when a failure time say, T cannot be observed directly but can only be determined to lie in an interval obtained from a series of inspection times. The frequentist approach for analysing interval-censored data has been developed for some time now. It is very common due to unavailability of software in the field of biological, medical and reliability studies to simplify the interval censoring structure of the data into that of a more standard right censoring situation by imputing the midpoints of the censoring intervals. In this research paper, we apply the Bayesian approach by employing Lindley's 1980, and Tierney and Kadane 1986 numerical approximation procedures when the survival data under consideration are interval-censored. The Bayesian approach to interval-censored data has barely been discussed in literature. The essence of this study is to explore and promote the Bayesian methods when the survival data been analysed are is interval-censored. We have considered only a parametric approach by assuming that the survival data follow a loglogistic distribution model. We illustrate the proposed methods with two real data sets. A simulation study is also carried out to compare the performances of the methods.
first_indexed 2025-11-15T10:05:00Z
format Article
id upm-43915
institution Universiti Putra Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T10:05:00Z
publishDate 2015
publisher Taylor & Francis
recordtype eprints
repository_type Digital Repository
spelling upm-439152018-04-09T07:50:49Z http://psasir.upm.edu.my/id/eprint/43915/ Bayesian statistical inference of loglogistic model with interval-censored lifetime data Guure, Chris Bambey Ibrahim, Noor Akma Dwomoh, Duah Bosomprah, Samuel The properties of Palm Oil (PO) and Coconut Oil (CO) offer the potential for transformers Interval-censored data arise when a failure time say, T cannot be observed directly but can only be determined to lie in an interval obtained from a series of inspection times. The frequentist approach for analysing interval-censored data has been developed for some time now. It is very common due to unavailability of software in the field of biological, medical and reliability studies to simplify the interval censoring structure of the data into that of a more standard right censoring situation by imputing the midpoints of the censoring intervals. In this research paper, we apply the Bayesian approach by employing Lindley's 1980, and Tierney and Kadane 1986 numerical approximation procedures when the survival data under consideration are interval-censored. The Bayesian approach to interval-censored data has barely been discussed in literature. The essence of this study is to explore and promote the Bayesian methods when the survival data been analysed are is interval-censored. We have considered only a parametric approach by assuming that the survival data follow a loglogistic distribution model. We illustrate the proposed methods with two real data sets. A simulation study is also carried out to compare the performances of the methods. Taylor & Francis 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/43915/1/Bayesian%20statistical%20inference%20of%20the%20loglogistic%20model%20with%20interval-censored%20lifetime%20.pdf Guure, Chris Bambey and Ibrahim, Noor Akma and Dwomoh, Duah and Bosomprah, Samuel (2015) Bayesian statistical inference of loglogistic model with interval-censored lifetime data. Journal of Statistical Computation and Simulation, 85 (8). pp. 1567-1583. ISSN 0094-9655; ESSN:1563-5163
spellingShingle Guure, Chris Bambey
Ibrahim, Noor Akma
Dwomoh, Duah
Bosomprah, Samuel
Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title_full Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title_fullStr Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title_full_unstemmed Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title_short Bayesian statistical inference of loglogistic model with interval-censored lifetime data
title_sort bayesian statistical inference of loglogistic model with interval-censored lifetime data
url http://psasir.upm.edu.my/id/eprint/43915/
http://psasir.upm.edu.my/id/eprint/43915/1/Bayesian%20statistical%20inference%20of%20the%20loglogistic%20model%20with%20interval-censored%20lifetime%20.pdf