The Effect of Duration and Delay of Licensure on Risk of Crash
持照时长与延迟取证对交通事故风险的影响AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要明确使用同一个体的多次事故时间和个体随机效应，直接涉及微观纵向数据的相关性。
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持照时长与延迟取证对交通事故风险的影响
- 研究问题
- 如何区分持照时长与取证年龄对交通事故风险的关系，并在同一个体多次事故时间相关、存在右删失时进行估计？
- 方法与思路
- 作者使用个体特定的对数正态加速失效时间模型，以贝叶斯方法补全未观测失效时间和随机效应，并通过 Gibbs 算法计算。
- 材料陈述的贡献
- 摘要称方法可处理个体内相关、右删失和个体差异，提供个体风险估计；应用中持照时长比取证年龄更能预测事故风险。
- 阅读关注点
- 应核对持照时长与年龄的参数化、随机截距和斜率设定、删失及先验假设，以及后验预测检查和频率学派比较。
- 阅读边界
- 仅据 OpenAlex 索引摘要，稿件版本未注明；观察性记录中的预测关系不等于因果效应，未说明如何处理未观测混杂。
原文摘要
The driving history records of a sample of 13,794 Michigan public school students were followed for up to 13 years from their initial time-of-license to determine the separate effects of duration of licensure and delay of licensure on risk of crash. We propose a subject-specific lognormal accelerated failure time to model the expected time-to-crash as a function of age at time of licensure, duration of licensure, and a set of control covariates. When multiple time-to-crash measures are observed for an individual, within-subject correlation can create substantial bias in the estimation of the effect of duration of licensure under an independence model. Generalized estimating equations provide consistent estimators of the variance when independence is misspecified but do not correct for this bias. Full maximum likelihood models generally require numerical integration and differentiation, and in practice, parameter estimates were unattainable for the dataset of interest. We instead adopt a Bayesian approach, imputing the unobserved failure times and slope-intercept random effects to account for right censoring and between-subject variability. We implement this approach using a Gibbs algorithm. We assess model fit via posterior predictive distributions. Our approach also allows for subject-specific risk estimates based on subject-level history. We compare the repeated sampling properties of this approach with those obtained using some frequentist approaches, and find that duration of licensure is a stronger predictor of risk of crash than age of licensure.