纵向数据的量子回归与值低于检测极限和时间依赖的共变量-应用到碳纳米管和纳米纤维暴露的建模
I-Chen Chen1, Stephen J Bertke1, Matthew M Dahm1
1Division of Field Studies and Engineering, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, 1090 Tusculum Avenue, MS-R14, Cincinnati, OH 45226, USA.
Annals of work exposures and health
|August 14, 2024
概括
预测量子回归模型有效地处理左控环境暴露数据和时间依赖的共变量. 这种方法改善了职业健康数据的分析,并考虑到随时间变化的变化.
科学领域:
- 职业健康和环境科学 职业健康和环境科学
- 生物监测和暴露评估.
- 统计建模和数据分析.
背景情况:
- 纵向环境暴露和生物监测数据通常表现出在检测极限 (LOD) 以下的右倾斜和左边审查.
- 传统的日志转换方法假定日志正常分布,这可能不成立,导致偏差或低效的暴露平均值建模.
- 纵向研究中的共变量可以随着时间的推移而变化,这给标准的统计分析带来了挑战.
研究的目的:
- 开发预测量子回归模型,以解决左边审查和时间依赖的共变量.
- 量化评估过去和现在的共同变量对当前和未来暴露水平的预测能力.
- 通过审查的测量来改善纵向职业健康数据的分析.
主要方法:
- 将各种替代方法纳入量子回归框架.
- 使用一种方法来选择合适的类型的时间依赖性对共变量.
- 在模拟研究中使用多重随机值归算来处理时间依赖的共变量.
主要成果:
- 多重随机值赋值在与时间依赖的共变量模拟研究中表现出优于其他方法的性能.
- 在碳纳米管和纳米纤维暴露研究中应用了开发的方法来分析左边审查的元素碳测量.
- 在暴露研究中确定了与工人决定因素和工作任务相关的潜在时间依赖的共变量.
结论:
- 同变量的时间依赖性经常被忽视在纵向,左边审查的暴露数据的预测建模中,导致效率损失.
- 如果不考虑时间变化的共变量,则会导致回归参数估计效率低下.
- 拟议的方法有效地处理纵向,左边审查的生物监测数据中的时间变异共变量,通过量度来说明条件分布.
更多相关视频
09:50Impact Assessment of Repeated Exposure of Organotypic 3D Bronchial and Nasal Tissue Culture Models to Whole Cigarette Smoke
Published on: February 12, 2015
11.1K
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
10.7K
相关概念视频
01:14Parametric Survival Analysis: Weibull and Exponential Methods
390
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
390
01:19Survival Tree
73
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
73
01:05Noncompartmental Analysis: Mean Residence Time
123
According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
After the administration of a drug through intravenous bolus injection, the drug molecules are distributed throughout the body and remain there for varying periods. The MRT represents the average time these drug molecules stay in the...
123
01:18Introduction To Survival Analysis
199
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
199
01:15Drug Concentration Versus Time Correlation
690
The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
Two pivotal parameters are the minimum effective concentration (MEC) and the minimum toxic concentration (MTC). The MEC is the...
690
01:09Censoring Survival Data
72
Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different...
72