Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate

This study aims to extend the generalized exponential model (GEM) to include covariates in the presence of interval-censored data. The maximum likelihood estimator (MLE) was obtained for the parameter of the model formulated. Afterward, a thorough simulation study was carried out to evaluate the est...

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Main Authors: Alharbi, Nada, A., Jayanthi, A., Haizum, Ling, Wendy
Format: Article
Published: Oesterreichische Statistische Gesellschaft (OSG) 2022
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author Alharbi, Nada
A., Jayanthi
A., Haizum
Ling, Wendy
author_facet Alharbi, Nada
A., Jayanthi
A., Haizum
Ling, Wendy
author_sort Alharbi, Nada
collection UPM
description This study aims to extend the generalized exponential model (GEM) to include covariates in the presence of interval-censored data. The maximum likelihood estimator (MLE) was obtained for the parameter of the model formulated. Afterward, a thorough simulation study was carried out to evaluate the estimator's performance based on the values of bias, standard error (SE), and root mean square error (RMSE). The result indicated that the (SE) and (RMSE) decrease with the increase in sample sizes and decrease in censoring proportions. Finally, the performance of the Wald confidence interval estimation technique for the GE model with interval-censored data covariate was assessed by a coverage probability study at several censoring proportions and different sample sizes.
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institution Universiti Putra Malaysia
last_indexed 2024-03-06T11:12:44Z
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spelling upm.eprints-1003972023-12-26T04:34:40Z http://psasir.upm.edu.my/id/eprint/100397/ Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate Alharbi, Nada A., Jayanthi A., Haizum Ling, Wendy This study aims to extend the generalized exponential model (GEM) to include covariates in the presence of interval-censored data. The maximum likelihood estimator (MLE) was obtained for the parameter of the model formulated. Afterward, a thorough simulation study was carried out to evaluate the estimator's performance based on the values of bias, standard error (SE), and root mean square error (RMSE). The result indicated that the (SE) and (RMSE) decrease with the increase in sample sizes and decrease in censoring proportions. Finally, the performance of the Wald confidence interval estimation technique for the GE model with interval-censored data covariate was assessed by a coverage probability study at several censoring proportions and different sample sizes. Oesterreichische Statistische Gesellschaft (OSG) 2022-01-24 Article PeerReviewed Alharbi, Nada and A., Jayanthi and A., Haizum and Ling, Wendy (2022) Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate. Austrian Journal of Statistics, 51 (1). 52 - 69. ISSN 1026-597X https://www.ajs.or.at/index.php/ajs/article/view/1192 10.17713/ajs.v51i1.1192
spellingShingle Alharbi, Nada
A., Jayanthi
A., Haizum
Ling, Wendy
Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title_full Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title_fullStr Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title_full_unstemmed Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title_short Assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
title_sort assessing performance of the generalized exponential model in the presence of the interval censored data with covariate
work_keys_str_mv AT alharbinada assessingperformanceofthegeneralizedexponentialmodelinthepresenceoftheintervalcensoreddatawithcovariate
AT ajayanthi assessingperformanceofthegeneralizedexponentialmodelinthepresenceoftheintervalcensoreddatawithcovariate
AT ahaizum assessingperformanceofthegeneralizedexponentialmodelinthepresenceoftheintervalcensoreddatawithcovariate
AT lingwendy assessingperformanceofthegeneralizedexponentialmodelinthepresenceoftheintervalcensoreddatawithcovariate