运用Logistic回归模型识别建筑损伤严重程度的影响因素

IF 0.8 4区工程技术 Q4 ENGINEERING, CIVIL

Teknik Dergi Pub Date : 2020-03-01 DOI:10.18400/tekderg.470633

Özge A. Kale, S. Baradan

{"title":"运用Logistic回归模型识别建筑损伤严重程度的影响因素","authors":"Özge A. Kale, S. Baradan","doi":"10.18400/tekderg.470633","DOIUrl":null,"url":null,"abstract":"Consequently, majority of studies in occupational safety leaned towards describing accidents with the aid of surveys and d escriptive statistics. This study intends to fill this gap by using inferential statistics to identify the factors that contribute to severity of injuries. Subsequently, cooperation with Social Security Institute of Turkey was achieved and an extensive archival study was performed. The information acquired from open-ended questions in forms were reorganized to be identified as variables. Categorically identified data set were analyzed statistically by using binary logistic regression analyses. The findings of the study showed that work experience, accident type, unsafe condition, unsafe act have statistically significant influence on Injury Severity Score.","PeriodicalId":49442,"journal":{"name":"Teknik Dergi","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Identifying Factors that Contribute to Severity of Construction Injuries using Logistic Regression Model\",\"authors\":\"Özge A. Kale, S. Baradan\",\"doi\":\"10.18400/tekderg.470633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Consequently, majority of studies in occupational safety leaned towards describing accidents with the aid of surveys and d escriptive statistics. This study intends to fill this gap by using inferential statistics to identify the factors that contribute to severity of injuries. Subsequently, cooperation with Social Security Institute of Turkey was achieved and an extensive archival study was performed. The information acquired from open-ended questions in forms were reorganized to be identified as variables. Categorically identified data set were analyzed statistically by using binary logistic regression analyses. The findings of the study showed that work experience, accident type, unsafe condition, unsafe act have statistically significant influence on Injury Severity Score.\",\"PeriodicalId\":49442,\"journal\":{\"name\":\"Teknik Dergi\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teknik Dergi\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.18400/tekderg.470633\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teknik Dergi","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.18400/tekderg.470633","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}

引用次数: 18

摘要

因此，大多数职业安全研究倾向于借助调查和描述性统计来描述事故。本研究旨在填补这一空白，利用推论统计来确定因素，有助于伤害的严重程度。后来，与土耳其社会保障研究所合作，进行了广泛的档案研究。从表格中开放性问题获得的信息被重新组织为变量。分类识别的数据集采用二元逻辑回归分析进行统计分析。研究结果表明，工作经历、事故类型、不安全状况、不安全行为对伤害严重程度评分有显著的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Identifying Factors that Contribute to Severity of Construction Injuries using Logistic Regression Model

Consequently, majority of studies in occupational safety leaned towards describing accidents with the aid of surveys and d escriptive statistics. This study intends to fill this gap by using inferential statistics to identify the factors that contribute to severity of injuries. Subsequently, cooperation with Social Security Institute of Turkey was achieved and an extensive archival study was performed. The information acquired from open-ended questions in forms were reorganized to be identified as variables. Categorically identified data set were analyzed statistically by using binary logistic regression analyses. The findings of the study showed that work experience, accident type, unsafe condition, unsafe act have statistically significant influence on Injury Severity Score.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Teknik Dergi 工程技术-工程：土木

自引率

30.80%

发文量

审稿时长

>12 weeks

期刊介绍： The scope of Teknik Dergi is naturally confined with the subjects falling in the area of civil engineering. However, the area of civil engineering has recently been significantly enlarged, even the definition of civil engineering has somewhat changed. Half a century ago, engineering was simply defined as “the art of using and converting the natural resources for the benefit of the mankind”. Today, the same objective is expected to be realised (i) by complying with the desire and expectations of the people concerned and (ii) without wasting the resources and within the sustainability principles. This change has required an interaction between engineering and social and administrative sciences. Some subjects at the borderline between civil engineering and social and administrative sciences have consequently been included in the area of civil engineering. Teknik Dergi defines its scope in line with this understanding. However, it requires the papers falling in the borderline to have a significant component of civil engineering.