Non-mixture cure model for interval censored data: a simulation study

With the ongoing advance in the medical sciences, we may quite often encounter data sets where some patients have been cured from disease. Standard survival models are usually not appropriate for modeling such data because they simply do not take into account the possibility of cure. In this article...

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Main Authors: Taweab, Fauzia, Ibrahim, Noor Akma, Arasan, Jayanthi, Abu Bakar, Mohd Rizam
Format: Article
Language:English
Published: Institute for Mathematical Research, Universiti Putra Malaysia 2014
Online Access:http://psasir.upm.edu.my/id/eprint/39049/
http://psasir.upm.edu.my/id/eprint/39049/1/39049.pdf
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author Taweab, Fauzia
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
author_facet Taweab, Fauzia
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
author_sort Taweab, Fauzia
building UPM Institutional Repository
collection Online Access
description With the ongoing advance in the medical sciences, we may quite often encounter data sets where some patients have been cured from disease. Standard survival models are usually not appropriate for modeling such data because they simply do not take into account the possibility of cure. In this article, a non-mixture cure model is proposed based on lognormal distribution when the exact time of the event of disease is subject to interval censoring. The maximum likelihood estimation (MLE) method is implemented to estimate the parameters and a simulation study is conducted to assess the performance of the estimators under various conditions. The study results demonstrate that the bias, standard error, and root mean squared error values of the parameters estimates decrease with the increase in sample size and that the estimation method is more robust for data sets that have low censoring rates.
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spelling upm-390492015-09-04T11:04:42Z http://psasir.upm.edu.my/id/eprint/39049/ Non-mixture cure model for interval censored data: a simulation study Taweab, Fauzia Ibrahim, Noor Akma Arasan, Jayanthi Abu Bakar, Mohd Rizam With the ongoing advance in the medical sciences, we may quite often encounter data sets where some patients have been cured from disease. Standard survival models are usually not appropriate for modeling such data because they simply do not take into account the possibility of cure. In this article, a non-mixture cure model is proposed based on lognormal distribution when the exact time of the event of disease is subject to interval censoring. The maximum likelihood estimation (MLE) method is implemented to estimate the parameters and a simulation study is conducted to assess the performance of the estimators under various conditions. The study results demonstrate that the bias, standard error, and root mean squared error values of the parameters estimates decrease with the increase in sample size and that the estimation method is more robust for data sets that have low censoring rates. Institute for Mathematical Research, Universiti Putra Malaysia 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/39049/1/39049.pdf Taweab, Fauzia and Ibrahim, Noor Akma and Arasan, Jayanthi and Abu Bakar, Mohd Rizam (2014) Non-mixture cure model for interval censored data: a simulation study. Malaysian Journal of Mathematical Sciences, 8 (S). pp. 37-44. ISSN 1823-8343; ESSN: 2289-750X http://einspem.upm.edu.my/journal/fullpaper/vol8soct/4.%20Fauzia%20Taweab%20EDITED.pdf
spellingShingle Taweab, Fauzia
Ibrahim, Noor Akma
Arasan, Jayanthi
Abu Bakar, Mohd Rizam
Non-mixture cure model for interval censored data: a simulation study
title Non-mixture cure model for interval censored data: a simulation study
title_full Non-mixture cure model for interval censored data: a simulation study
title_fullStr Non-mixture cure model for interval censored data: a simulation study
title_full_unstemmed Non-mixture cure model for interval censored data: a simulation study
title_short Non-mixture cure model for interval censored data: a simulation study
title_sort non-mixture cure model for interval censored data: a simulation study
url http://psasir.upm.edu.my/id/eprint/39049/
http://psasir.upm.edu.my/id/eprint/39049/
http://psasir.upm.edu.my/id/eprint/39049/1/39049.pdf