高速公路事故伤害严重程度的部分受约束的潜在类别分析:从区域数据源中调查离散空间异质性
Jiabin Wu1, Yiming Bie2, Qihang Li3
1School of Management, Foshan University, Foshan 528225, China.
Accident; analysis and prevention
|November 14, 2024
概括
交通事故伤害严重程度受到随时间和空间而变化的因素的影响. 了解这些动态是制定有效的交通安全策略和预防伤害的关键.
科学领域:
- 运输安全运输安全
- 交通工程是交通工程.
- 伤害预防 预防伤害
背景情况:
- 碰撞伤害的严重程度受到不可观察的因素的影响,导致空间和时间的变化.
- 忽视空间异质性和时间不稳定性可能会导致偏差估计,并导致无效的安全策略.
研究的目的:
- 同时分析影响交通事故伤害严重程度的因素的空间异质性和时间不稳定性.
- 确定影响碰撞伤害严重程度及其动态影响的关键因素.
主要方法:
- 利用来自奥斯大都市区 (2017-2019) 的交通事故数据.
- 采用隐性类逻辑模型,通过县级数据结合空间异质性.
- 应用了一种部分受约束的方法,用于年度建模以评估时间不稳定性.
主要成果:
- 确定了许多影响碰撞伤害严重程度的重要因素.
- 在碰撞地点,照明,驾驶员人口统计和车辆特征等因素的影响中发现了显著的时间不稳定性.
- 几种解释变量表明伤害严重程度的时间变化影响.
结论:
- 空间和时间动态对于准确的碰撞伤害严重程度分析至关重要.
- 这些发现为了解碰撞机制和改善交通安全措施提供了宝贵的参考资料.
- 时间因素的不稳定性需要适应性安全策略.
相关概念视频
Hypothesis Test for Test of Independence
3.5K
The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
H0: The two variables (factors)...
3.5K
Structural Classification of Joints
3.2K
Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
A fibrous joint is where the adjacent bones are united by fibrous connective...
3.2K
Statistical Methods for Analyzing Epidemiological Data
308
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
308
Functional Classification of Joints
3.8K
Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
An...
3.8K
Hazard Rate
89
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
89
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
49
Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...
49


