Non-parametric maximum likelihood estimation of cure fraction for interval survival data.

In cancer clinical trials, a significant fraction of patients can be cured, that is, the symptoms of the disease are completely eliminated, so that it will never recurs. In this article the focus is on the estimation of the proportion of patients who are cured. The Nonparametric maximum likelihood e...

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Main Authors: I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma
Format: Article
Language:English
English
Published: CESER Publications 2011
Online Access:http://psasir.upm.edu.my/id/eprint/24825/
http://psasir.upm.edu.my/id/eprint/24825/1/Non.pdf
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author I. Aljawadi, Bader Ahmad
Abu Bakar, Mohd Rizam
Ibrahim, Noor Akma
author_facet I. Aljawadi, Bader Ahmad
Abu Bakar, Mohd Rizam
Ibrahim, Noor Akma
author_sort I. Aljawadi, Bader Ahmad
building UPM Institutional Repository
collection Online Access
description In cancer clinical trials, a significant fraction of patients can be cured, that is, the symptoms of the disease are completely eliminated, so that it will never recurs. In this article the focus is on the estimation of the proportion of patients who are cured. The Nonparametric maximum likelihood estimation method is used for interval censored data based on the bounded cumulative hazard (BCH) model. We implement the Turnbull algorithm for the survival function estimation using EM algorithm. The analysis shows the analytical solution of the estimating equations for the cure proportion followed by a simulation study.
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publishDate 2011
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spelling upm-248252015-09-23T03:00:31Z http://psasir.upm.edu.my/id/eprint/24825/ Non-parametric maximum likelihood estimation of cure fraction for interval survival data. I. Aljawadi, Bader Ahmad Abu Bakar, Mohd Rizam Ibrahim, Noor Akma In cancer clinical trials, a significant fraction of patients can be cured, that is, the symptoms of the disease are completely eliminated, so that it will never recurs. In this article the focus is on the estimation of the proportion of patients who are cured. The Nonparametric maximum likelihood estimation method is used for interval censored data based on the bounded cumulative hazard (BCH) model. We implement the Turnbull algorithm for the survival function estimation using EM algorithm. The analysis shows the analytical solution of the estimating equations for the cure proportion followed by a simulation study. CESER Publications 2011 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/24825/1/Non.pdf I. Aljawadi, Bader Ahmad and Abu Bakar, Mohd Rizam and Ibrahim, Noor Akma (2011) Non-parametric maximum likelihood estimation of cure fraction for interval survival data. International Journal of Applied Mathematics and Statistics, 21 (J11). 118 - 130. ISSN 0973-7545 http://www.ceser.in/ijamas.html English
spellingShingle I. Aljawadi, Bader Ahmad
Abu Bakar, Mohd Rizam
Ibrahim, Noor Akma
Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title_full Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title_fullStr Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title_full_unstemmed Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title_short Non-parametric maximum likelihood estimation of cure fraction for interval survival data.
title_sort non-parametric maximum likelihood estimation of cure fraction for interval survival data.
url http://psasir.upm.edu.my/id/eprint/24825/
http://psasir.upm.edu.my/id/eprint/24825/
http://psasir.upm.edu.my/id/eprint/24825/1/Non.pdf