Model-building of multiple binary logit using model averaging
Many researchers had been carried out on the study of statistical modelling, making it easier for new researchers in many sectors (social sciences, economics, medical, and etc.) to obtain knowledge in order to ease their research study. Nevertheless, there is still no agreed guidelines in obtaining...
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Science Publishing Corporation
2018
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| Online Access: | http://eprints.uthm.edu.my/4407/ |
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| author | Mohd Padzil, Siti Aisyah Pillay, Khuneswari Gopal Mohd Salleh, Rohayu |
| author_facet | Mohd Padzil, Siti Aisyah Pillay, Khuneswari Gopal Mohd Salleh, Rohayu |
| author_sort | Mohd Padzil, Siti Aisyah |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Many researchers had been carried out on the study of statistical modelling, making it easier for new researchers in many sectors (social sciences, economics, medical, and etc.) to obtain knowledge in order to ease their research study. Nevertheless, there is still no agreed guidelines in obtaining the best model for multiple binary logit (MBL) using model averaging (MA). This research will demonstrate the proper guidelines to obtain best MBL model by using MA. Upper Gastrointestinal Bleed (UGIB) data were studied to illustrate the process of model-building using the proposed guidelines. This study will pinpoint the factors with high possibility leading to mortality of UGIB patients using obtained best model. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were used to compute the weights in model averaging method. The performance of the models was computed by using Root mean square error (RMSE) and mean absolute error (MAE). Model obtained by using BIC weights showed a better performance since the RMSE and MAE values are lower compared to model obtained using AICc weights. The factors that affects the survivability of UGIB patients are shock score, comorbidity and rebleed. In conclusion, model-building of multiple binary logit using model averaging showed a better performance when using BIC. |
| format | Article |
| id | my.uthm.eprints-4407 |
| institution | Universiti Tun Hussein Onn Malaysia |
| publishDate | 2018 |
| publisher | Science Publishing Corporation |
| record_format | eprints |
| spelling | my.uthm.eprints-44072021-12-02T07:18:32Z http://eprints.uthm.edu.my/4407/ Model-building of multiple binary logit using model averaging Mohd Padzil, Siti Aisyah Pillay, Khuneswari Gopal Mohd Salleh, Rohayu QA273-280 Probabilities. Mathematical statistics Many researchers had been carried out on the study of statistical modelling, making it easier for new researchers in many sectors (social sciences, economics, medical, and etc.) to obtain knowledge in order to ease their research study. Nevertheless, there is still no agreed guidelines in obtaining the best model for multiple binary logit (MBL) using model averaging (MA). This research will demonstrate the proper guidelines to obtain best MBL model by using MA. Upper Gastrointestinal Bleed (UGIB) data were studied to illustrate the process of model-building using the proposed guidelines. This study will pinpoint the factors with high possibility leading to mortality of UGIB patients using obtained best model. Corrected Akaike Information Criteria (AICc) and Bayesian Information Criteria (BIC) were used to compute the weights in model averaging method. The performance of the models was computed by using Root mean square error (RMSE) and mean absolute error (MAE). Model obtained by using BIC weights showed a better performance since the RMSE and MAE values are lower compared to model obtained using AICc weights. The factors that affects the survivability of UGIB patients are shock score, comorbidity and rebleed. In conclusion, model-building of multiple binary logit using model averaging showed a better performance when using BIC. Science Publishing Corporation 2018 Article PeerReviewed Mohd Padzil, Siti Aisyah and Pillay, Khuneswari Gopal and Mohd Salleh, Rohayu (2018) Model-building of multiple binary logit using model averaging. International Journal of Engineering and Technology, 7 (4.3). pp. 224-228. ISSN 2227-524X |
| spellingShingle | QA273-280 Probabilities. Mathematical statistics Mohd Padzil, Siti Aisyah Pillay, Khuneswari Gopal Mohd Salleh, Rohayu Model-building of multiple binary logit using model averaging |
| title | Model-building of multiple binary logit using model averaging |
| title_full | Model-building of multiple binary logit using model averaging |
| title_fullStr | Model-building of multiple binary logit using model averaging |
| title_full_unstemmed | Model-building of multiple binary logit using model averaging |
| title_short | Model-building of multiple binary logit using model averaging |
| title_sort | model-building of multiple binary logit using model averaging |
| topic | QA273-280 Probabilities. Mathematical statistics |
| url | http://eprints.uthm.edu.my/4407/ |
| url_provider | http://eprints.uthm.edu.my/ |