{"_buckets": {"deposit": "1ec554df-1a68-410b-b0a4-b22ad4fdba8a"}, "_deposit": {"created_by": 20, "id": "9344", "owner": "20", "owners": [20], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "9344"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00009344", "sets": ["1582963436320", "1707206634013"]}, "author_link": [], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "ANALYSIS AND FORECASTING OF ROAD TRAFFIC ACCIDENTS IN YANGON MUNICIPAL AREA (2014-2018) (Thiri Ko, 2019)", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Road accident in Myanmar is the thirteenth major cause of death after kidney disease and diarrhoea disease. The ultimate goal of this thesis is to use Poisson regression to fit a model to the secondary data which was obtained from No (2) Office of Traffic Police (Yangon) on the number of people killed and injured by road accidents in Yangon city from 2014-2018. The type of causes of accidental crash, townships with the highest rate of road accident in Yangon against time (in years) are explored in this study. The result of Poisson analysis showed that there was over dispersion in the data. Negative binomial regression analysis was therefore used to validate the Poisson regression model. It was clear that the negative binomial regression model was the best fit for the data but for the occurrence of number of people who were killed and injured given the selected townships (Hlaingtharyar, Insein, Mayangon and Mingalardon) and types of crash causes, Poisson regression model is fitter than Negative binomial regression model for that data analysis. In the long run, the number of people in both killed and injured in Yangon would be gradually decreased. Finally, the result showed that the driver fault and over speeding were the main causes of death in road traffic accidents in Yangon (Municipal Area)."}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2024-03-01"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Thiri Ko, M.Econ. Stats Roll.1, 2019.pdf", "filesize": [{"value": "2.2 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_0", "mimetype": "application/pdf", "size": 2200000.0, "url": {"url": "https://meral.edu.mm/record/9344/files/Thiri Ko, M.Econ. Stats Roll.1, 2019.pdf"}, "version_id": "16c057b2-23f0-40f7-ab4b-6a7dc4b3e14c"}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "Yangon University of Economics", "subitem_supervisor(s)": [{"subitem_supervisor": "Daw Soe Soe Lwin"}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thiri Ko"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Other"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Thesis"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-11-01"}, "item_title": "ANALYSIS AND FORECASTING OF ROAD TRAFFIC ACCIDENTS IN YANGON MUNICIPAL AREA (2014-2018) (Thiri Ko, 2019)", "item_type_id": "21", "owner": "20", "path": ["1582963436320", "1707206634013"], "permalink_uri": "https://meral.edu.mm/records/9344", "pubdate": {"attribute_name": "Deposit date", "attribute_value": "2024-03-01"}, "publish_date": "2024-03-01", "publish_status": "0", "recid": "9344", "relation": {}, "relation_version_is_last": true, "title": ["ANALYSIS AND FORECASTING OF ROAD TRAFFIC ACCIDENTS IN YANGON MUNICIPAL AREA (2014-2018) (Thiri Ko, 2019)"], "weko_shared_id": -1}