Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate
This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusion...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Austrian Society for Statistics
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/87943/ http://psasir.upm.edu.my/id/eprint/87943/1/ABSTRACT.pdf |
| _version_ | 1848860526781661184 |
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| author | Azid @ Maarof, Nur Niswah Naslina Arasan, Jayanthi Zulkafli, Hani Syahida Mohd Bakri, Adam |
| author_facet | Azid @ Maarof, Nur Niswah Naslina Arasan, Jayanthi Zulkafli, Hani Syahida Mohd Bakri, Adam |
| author_sort | Azid @ Maarof, Nur Niswah Naslina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusions were drawn based on the results of bias, standard error and root mean square error at different settings. Following that, another simulation study was carried out to compare the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations at different combinations of sample sizes and censoring levels. The results show that standard error and root mean square error values of the parameter estimates increase with the increase in censoring proportions and decrease in the number of sample size. This indicates that the estimates perform better when sample sizes are larger and censoring proportions are lower. The performance of the proposed modifications of the Cox-Snell residuals showed that they perform slightly better than existing method. |
| first_indexed | 2025-11-15T12:46:38Z |
| format | Article |
| id | upm-87943 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:46:38Z |
| publishDate | 2020 |
| publisher | Austrian Society for Statistics |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-879432021-10-07T02:12:49Z http://psasir.upm.edu.my/id/eprint/87943/ Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate Azid @ Maarof, Nur Niswah Naslina Arasan, Jayanthi Zulkafli, Hani Syahida Mohd Bakri, Adam This research focuses on assessing the goodness of fit for the Gompertz model in the presence of right and interval censored data with covariate. The performance of the maximum likelihood estimates was evaluated via a simulation study at various censoring proportions and sample sizes. The conclusions were drawn based on the results of bias, standard error and root mean square error at different settings. Following that, another simulation study was carried out to compare the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations at different combinations of sample sizes and censoring levels. The results show that standard error and root mean square error values of the parameter estimates increase with the increase in censoring proportions and decrease in the number of sample size. This indicates that the estimates perform better when sample sizes are larger and censoring proportions are lower. The performance of the proposed modifications of the Cox-Snell residuals showed that they perform slightly better than existing method. Austrian Society for Statistics 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87943/1/ABSTRACT.pdf Azid @ Maarof, Nur Niswah Naslina and Arasan, Jayanthi and Zulkafli, Hani Syahida and Mohd Bakri, Adam (2020) Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate. Austrian Journal of Statistics, 49 (3 spec.). 57 - 71. ISSN 1026-597X https://www.ajs.or.at/index.php/ajs/article/view/1085 10.17713/ajs.v49i3.1085 |
| spellingShingle | Azid @ Maarof, Nur Niswah Naslina Arasan, Jayanthi Zulkafli, Hani Syahida Mohd Bakri, Adam Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title | Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title_full | Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title_fullStr | Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title_full_unstemmed | Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title_short | Assessing the goodness of fit of the Gompertz model in the presence of right and interval censored data with covariate |
| title_sort | assessing the goodness of fit of the gompertz model in the presence of right and interval censored data with covariate |
| url | http://psasir.upm.edu.my/id/eprint/87943/ http://psasir.upm.edu.my/id/eprint/87943/ http://psasir.upm.edu.my/id/eprint/87943/ http://psasir.upm.edu.my/id/eprint/87943/1/ABSTRACT.pdf |