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...

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Main Authors: Khuneswari Gopal Pillay, Siti Aisyah Mohd Padzil, Rohayu Mohd Salleh, Noraini Abdullah
Format: Article
Language:English
English
Published: 2018
Subjects:
Online Access:https://eprints.ums.edu.my/id/eprint/25212/1/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients.pdf
https://eprints.ums.edu.my/id/eprint/25212/7/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients1.pdf
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author Khuneswari Gopal Pillay
Siti Aisyah Mohd Padzil
Rohayu Mohd Salleh
Noraini Abdullah
author_facet Khuneswari Gopal Pillay
Siti Aisyah Mohd Padzil
Rohayu Mohd Salleh
Noraini Abdullah
author_sort Khuneswari Gopal Pillay
collection UMS
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.
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spelling ums.eprints-252122020-06-18T15:49:56Z https://eprints.ums.edu.my/id/eprint/25212/ Model Selection and Model Averaging on Mortality of Upper Gastrointestinal Bleed Patients Khuneswari Gopal Pillay Siti Aisyah Mohd Padzil Rohayu Mohd Salleh Noraini Abdullah HB Economic theory. Demography R Medicine (General) 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. 2018-11 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/25212/1/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients.pdf text en https://eprints.ums.edu.my/id/eprint/25212/7/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients1.pdf Khuneswari Gopal Pillay and Siti Aisyah Mohd Padzil and Rohayu Mohd Salleh and Noraini Abdullah (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 HB Economic theory. Demography
R Medicine (General)
Khuneswari Gopal Pillay
Siti Aisyah Mohd Padzil
Rohayu Mohd Salleh
Noraini Abdullah
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 HB Economic theory. Demography
R Medicine (General)
url https://eprints.ums.edu.my/id/eprint/25212/1/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients.pdf
https://eprints.ums.edu.my/id/eprint/25212/7/Model%20Selection%20and%20Model%20Averaging%20on%20Mortality%20of%20Upper%20Gastrointestinal%20Bleed%20Patients1.pdf
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