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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Oesterreichische Statistische Gesellschaft (OSG)
2022
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oai:psasir.upm.edu.my:100397 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 |
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UPM IR |
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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. |
| format |
Article |
| author |
Alharbi, Nada A., Jayanthi A., Haizum Ling, Wendy |
| 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 |
| author_facet |
Alharbi, Nada A., Jayanthi A., Haizum Ling, Wendy |
| author_sort |
Alharbi, Nada |
| title |
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_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_sort |
assessing performance of the generalized exponential model in the presence of the interval censored data with covariate |
| publisher |
Oesterreichische Statistische Gesellschaft (OSG) |
| publishDate |
2022 |
| _version_ |
1819301183492194304 |
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13.4562235 |