Model selection and model averaging on mortality of upper gastrointestinal bleed patients
Model Selection (MS) is known to produce uncertainty into model-building process. Besides that, the process of MS is complex and time consuming. Therefore, Model Averaging (MA) had been proposed as an alternative to overcome the issues. This research will provide guidelines of obtaining best model b...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
International Organization of Scientific Research (IOSR)
2018
|
| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/4411/ http://eprints.uthm.edu.my/4411/1/AJ%202018%20%28762%29%20Model%20selection%20and%20model%20averaging%20on%20mortality%20of%20upper%20gastrointestinal%20bleed%20patients.pdf |
| _version_ | 1848888280377982976 |
|---|---|
| author | Pillay, Khuneswari Gopal Mohd Padzil, Siti Aisyah Mohd Salleh, Rohayu Abdullah, Noraini |
| author_facet | Pillay, Khuneswari Gopal Mohd Padzil, Siti Aisyah Mohd Salleh, Rohayu Abdullah, Noraini |
| author_sort | Pillay, Khuneswari Gopal |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Model Selection (MS) is known to produce uncertainty into model-building process. Besides that, the process of MS is complex and time consuming. Therefore, Model Averaging (MA) had been proposed as an alternative to overcome the issues. This research will provide guidelines of obtaining best model by using two modelling approach which are Model Selection (MS) and Model Averaging (MA) and compares the performance of both methods. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were applied in the model-building using MS to help determine the best model. In MA process, model selection criteria are needed to compute the weights of each possible models. Two model selection criteria (AICcand BIC) were compared to observe which will produce model with a better performance. For guidelines illustration, data of Upper Gastrointestinal Bleed (UGIB) were explored to identify influential factors which leads to the mortality of patients. At the end of the study, best model using MA shown to have a better performance andAICc is proven to be a better model selection criterion approach in MA. In conclusion, the most significant factors for mortality of UGIB patients were identified to be shock score, comorbidity and rebleed. |
| first_indexed | 2025-11-15T20:07:46Z |
| format | Article |
| id | uthm-4411 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:07:46Z |
| publishDate | 2018 |
| publisher | International Organization of Scientific Research (IOSR) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-44112021-12-02T07:28:58Z http://eprints.uthm.edu.my/4411/ Model selection and model averaging on mortality of upper gastrointestinal bleed patients Pillay, Khuneswari Gopal Mohd Padzil, Siti Aisyah Mohd Salleh, Rohayu Abdullah, Noraini T57.6-57.97 Operations research. Systems analysis Model Selection (MS) is known to produce uncertainty into model-building process. Besides that, the process of MS is complex and time consuming. Therefore, Model Averaging (MA) had been proposed as an alternative to overcome the issues. This research will provide guidelines of obtaining best model by using two modelling approach which are Model Selection (MS) and Model Averaging (MA) and compares the performance of both methods. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were applied in the model-building using MS to help determine the best model. In MA process, model selection criteria are needed to compute the weights of each possible models. Two model selection criteria (AICcand BIC) were compared to observe which will produce model with a better performance. For guidelines illustration, data of Upper Gastrointestinal Bleed (UGIB) were explored to identify influential factors which leads to the mortality of patients. At the end of the study, best model using MA shown to have a better performance andAICc is proven to be a better model selection criterion approach in MA. In conclusion, the most significant factors for mortality of UGIB patients were identified to be shock score, comorbidity and rebleed. International Organization of Scientific Research (IOSR) 2018 Article PeerReviewed text en http://eprints.uthm.edu.my/4411/1/AJ%202018%20%28762%29%20Model%20selection%20and%20model%20averaging%20on%20mortality%20of%20upper%20gastrointestinal%20bleed%20patients.pdf Pillay, Khuneswari Gopal and Mohd Padzil, Siti Aisyah and Mohd Salleh, Rohayu and Abdullah, Noraini (2018) Model selection and model averaging on mortality of upper gastrointestinal bleed patients. IOSR Journal of Dental and Medical Sciences (IOSR-JDMS, 17 (11). pp. 68-78. ISSN 2279-0853 |
| spellingShingle | T57.6-57.97 Operations research. Systems analysis Pillay, Khuneswari Gopal Mohd Padzil, Siti Aisyah Mohd Salleh, Rohayu Abdullah, Noraini Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title | Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title_full | Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title_fullStr | Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title_full_unstemmed | Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title_short | Model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| title_sort | model selection and model averaging on mortality of upper gastrointestinal bleed patients |
| topic | T57.6-57.97 Operations research. Systems analysis |
| url | http://eprints.uthm.edu.my/4411/ http://eprints.uthm.edu.my/4411/1/AJ%202018%20%28762%29%20Model%20selection%20and%20model%20averaging%20on%20mortality%20of%20upper%20gastrointestinal%20bleed%20patients.pdf |