Applications of Bladder Cancer Data Using a Modified Log-Logistic Model
In information science, modern and advanced computational methods and tools are often used to build predictive models for time-to-event data analysis. Such predictive models based on previously collected data from patients can support decision-making and prediction of clinical data. Therefore, a new...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1155/2022/6600278 |
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| _version_ | 1850167838272126976 |
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| author | Mohamed Kayid |
| author_facet | Mohamed Kayid |
| author_sort | Mohamed Kayid |
| collection | DOAJ |
| description | In information science, modern and advanced computational methods and tools are often used to build predictive models for time-to-event data analysis. Such predictive models based on previously collected data from patients can support decision-making and prediction of clinical data. Therefore, a new simple and flexible modified log-logistic model is presented in this paper. Then, some basic statistical and reliability properties are discussed. Also, a graphical method for determining the data from the log-logistic or the proposed modified model is presented. Some methods are applied to estimate the parameters of the presented model. A simulation study is conducted to investigate the consistency and behavior of the discussed estimators. Finally, the model is fitted to two data sets and compared with some other candidates. |
| format | Article |
| id | doaj-art-dfe25fe8673340eca772fff07af57565 |
| institution | OA Journals |
| issn | 1754-2103 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-dfe25fe8673340eca772fff07af575652025-08-20T02:21:07ZengWileyApplied Bionics and Biomechanics1754-21032022-01-01202210.1155/2022/6600278Applications of Bladder Cancer Data Using a Modified Log-Logistic ModelMohamed Kayid0Department of Statistics and Operations ResearchIn information science, modern and advanced computational methods and tools are often used to build predictive models for time-to-event data analysis. Such predictive models based on previously collected data from patients can support decision-making and prediction of clinical data. Therefore, a new simple and flexible modified log-logistic model is presented in this paper. Then, some basic statistical and reliability properties are discussed. Also, a graphical method for determining the data from the log-logistic or the proposed modified model is presented. Some methods are applied to estimate the parameters of the presented model. A simulation study is conducted to investigate the consistency and behavior of the discussed estimators. Finally, the model is fitted to two data sets and compared with some other candidates.http://dx.doi.org/10.1155/2022/6600278 |
| spellingShingle | Mohamed Kayid Applications of Bladder Cancer Data Using a Modified Log-Logistic Model Applied Bionics and Biomechanics |
| title | Applications of Bladder Cancer Data Using a Modified Log-Logistic Model |
| title_full | Applications of Bladder Cancer Data Using a Modified Log-Logistic Model |
| title_fullStr | Applications of Bladder Cancer Data Using a Modified Log-Logistic Model |
| title_full_unstemmed | Applications of Bladder Cancer Data Using a Modified Log-Logistic Model |
| title_short | Applications of Bladder Cancer Data Using a Modified Log-Logistic Model |
| title_sort | applications of bladder cancer data using a modified log logistic model |
| url | http://dx.doi.org/10.1155/2022/6600278 |
| work_keys_str_mv | AT mohamedkayid applicationsofbladdercancerdatausingamodifiedloglogisticmodel |