CVtreeMLE:使用数据适应性决策树和交叉验证的目标最大概率估计在R中的混合风险高效估计
David McCoy1, Alan Hubbard2, Mark Van der Laan2
1Division of Environmental Health Sciences, University of California, Berkeley, CA, United States of America.
Journal of open source software
|July 3, 2023
概括
这项研究引入了一个新的R包,CVtreeMLE,用于分析混合暴露. 它使用决策树来为组合的环境暴露提供准确的因果推断,改进了传统方法.
科学领域:
- 生物统计学 生物统计学
- 流行病学 流行病学
- 环境健康科学 环境健康科学
背景情况:
- 混合暴露分析的传统方法通常依赖于参数模型或独立评估暴露,导致对联合影响的偏见估计.
- 现有的混合方法,如/拉索回归和主要成分回归,具有局限性,包括线性假设,用户定义的交互和解释性丧失.
- 诸如量子g计算和贝叶斯内核机器回归等先进的方法存在偏差或计算挑战,缺乏剂量反应关系的强有力的总结统计数据.
研究的目的:
- 引入一种新的非参数统计机器学习方法,用于混合暴露的因果推断.
- 提供一种可靠的方法,以识别数据适应性决定的决策树,用于混合暴露分析.
- 为目标参数提供可解释的结果和有效的推断,解决现有统计模型的局限性.
主要方法:
- 使用非参数决策树方法在联合暴露空间中识别分区,以解释结果差异.
- 采用一种新的决策树推断方法,通过不使用完整的数据集来识别和推断节点,避免了过拟合.
- CVtreeMLE R包是为了实现这些最先进的统计方法而开发的.
主要成果:
- CVtreeMLE包为混合暴露分析提供了一个灵活的,非参数替代潜在偏差的通用线性模型 (GLM).
- 它可以通过数据适应性来确定最适合的决策树来评估组合暴露.
- 提供可解释的结果和有效的统计推断,用于混合暴露的因果作用.
结论:
- 该CVtreeMLE R包为研究人员提供了先进的统计工具,用于在混合暴露环境中进行因果推理.
- 它克服了传统和现有的先进方法的局限性,通过提供灵活,非参数和可解释的方法.
- 有助于更准确地评估多种环境暴露对健康结果的联合影响.
相关概念视频
Strategies for Assessing and Addressing Confounding
121
Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
121
Survival Tree
117
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...
117
Mechanistic Models: Compartment Models in Individual and Population Analysis
65
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
65
Kaplan-Meier Approach
190
The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
190
Comparing the Survival Analysis of Two or More Groups
227
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
227
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
582
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
582


