同济大学学报（自然科学版）2012，Vol.40Issue(12)：1808-1813,6.DOI:10.3969/j.issn.0253-374x.2012.12.011
删失数据下事件持续时间多因素生存分析模型
Multivariate Survival Analysis Models for Incident Duration With Censored Data
摘要
Abstract
Traffic incident duration is one of the most important indexes in accident management studies. The semi-parametric proportional hazards model (Cox model) and parametric accelerated failure time model (AFT model) were employed for analysis of the association between multivariate incident durations and risk factors. With the three-year traffic incidents data collected from some freeways in Zhejiang Province, the Cox model and AFT model with covariates selected to remain in the model and survival probability of sensitivity to common covariates were illustrated and compared. Based on the Cox and the Log-logistic AFT models, the parameter estimates showed that six significant covariates were selected to remain in the estimated survival functions, including accident time, accident type, number of lanes occupied, number of the injured and accident of fatality. With regard to the most significant indicator variable (accident of fatality), the estimates of the survival probability curves for duration demonstrate that the AFT model give a higher sensitivity than the Cox model, and the Cox model is more appropriate for short time incident duration prediction. Moreover, survival analysis models can predict duration based on incident report and benefit rescue countermeasure and emergency aid decision after accidents.关键词
交通事件/持续时间/生存分析/比例风险模型/加速失效模型Key words
traffic incident/duration/survival analysis/proportional hazards model/accelerated failure time model分类
交通工程引用本文复制引用
蒋宏,方守恩,陈雨人..删失数据下事件持续时间多因素生存分析模型[J].同济大学学报（自然科学版）,2012,40(12):1808-1813,6.基金项目
国家"八六三"高技术研究发展计划(2007AA112233) （2007AA112233）
