Parametric estimation for partly interval-censored failure time data under Weibull distribution

This article discusses the parametric estimation in the existence of partly interval-censored failure time data. Partly interval-censored failure time data is composed of exact observations and interval-censored observations. This phenomenon often happens in clinical trials and health studies that a...

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Main Authors: Mohammad Alharpy, Azzah, Ibrahim, Noor Akma
Format: Article
Published: Scientific Publishing Center, University of Bahrain 2014
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author Mohammad Alharpy, Azzah
Ibrahim, Noor Akma
author_facet Mohammad Alharpy, Azzah
Ibrahim, Noor Akma
author_sort Mohammad Alharpy, Azzah
collection UPM
description This article discusses the parametric estimation in the existence of partly interval-censored failure time data. Partly interval-censored failure time data is composed of exact observations and interval-censored observations. This phenomenon often happens in clinical trials and health studies that are followed by periodic follow-ups. We have constructed a parametric estimation for this kind of failure time data under Weibull distributions by using direct approach (without imputation) and indirect approach (with multiple imputation technique). Simulation studies are established to assess the proposed estimate for survival function and to illustrate the difference between the two approaches. The simulation results indicate that the presented procedure works well for both approaches but the estimate under the indirect approach is better than the estimate under direct approach. A modified secondary data set from breast cancer study is used to illustrate the proposed estimation.
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spelling upm.eprints-348142015-12-23T03:05:01Z http://psasir.upm.edu.my/id/eprint/34814/ Parametric estimation for partly interval-censored failure time data under Weibull distribution Mohammad Alharpy, Azzah Ibrahim, Noor Akma This article discusses the parametric estimation in the existence of partly interval-censored failure time data. Partly interval-censored failure time data is composed of exact observations and interval-censored observations. This phenomenon often happens in clinical trials and health studies that are followed by periodic follow-ups. We have constructed a parametric estimation for this kind of failure time data under Weibull distributions by using direct approach (without imputation) and indirect approach (with multiple imputation technique). Simulation studies are established to assess the proposed estimate for survival function and to illustrate the difference between the two approaches. The simulation results indicate that the presented procedure works well for both approaches but the estimate under the indirect approach is better than the estimate under direct approach. A modified secondary data set from breast cancer study is used to illustrate the proposed estimation. Scientific Publishing Center, University of Bahrain 2014-06 Article PeerReviewed Mohammad Alharpy, Azzah and Ibrahim, Noor Akma (2014) Parametric estimation for partly interval-censored failure time data under Weibull distribution. Journal of Data Analysis and Operations Research, 1 (1). pp. 7-15. ISSN 2384-4671 http://journals.uob.edu.bh/JDAOR/contents/volume-14/articles/article-164
spellingShingle Mohammad Alharpy, Azzah
Ibrahim, Noor Akma
Parametric estimation for partly interval-censored failure time data under Weibull distribution
title Parametric estimation for partly interval-censored failure time data under Weibull distribution
title_full Parametric estimation for partly interval-censored failure time data under Weibull distribution
title_fullStr Parametric estimation for partly interval-censored failure time data under Weibull distribution
title_full_unstemmed Parametric estimation for partly interval-censored failure time data under Weibull distribution
title_short Parametric estimation for partly interval-censored failure time data under Weibull distribution
title_sort parametric estimation for partly interval censored failure time data under weibull distribution
work_keys_str_mv AT mohammadalharpyazzah parametricestimationforpartlyintervalcensoredfailuretimedataunderweibulldistribution
AT ibrahimnoorakma parametricestimationforpartlyintervalcensoredfailuretimedataunderweibulldistribution