使用有限混合的多变量受污染的正常线性混合模型进行分组的多轨迹建模
Tsung-I Lin1,2, Wan-Lun Wang3
1Institute of Statistics, National Chung Hsing University, Taichung, Taiwan.
Statistical methods in medical research
|January 12, 2026
概括
这项研究引入了新的统计模型,用于集群复杂的纵向数据,比如来自阿尔茨海默病神经成像计划 (ADNI) 的数据. 这些模型在分组数据分析中有效处理各种进展模式和异常观察.
科学领域:
- 生物统计学 生物统计学
- 纵向数据分析 纵向数据分析
- 机器学习 机器学习
背景情况:
- 多变量纵向数据分析对于理解复杂的生物过程至关重要.
- 阿尔茨海默病神经成像计划 (ADNI) 提出了挑战,原因是不同的进展模式和非典型的观察.
- 现有的方法在建模和集群这些异质的分组数据方面遇到了困难.
研究的目的:
- 为模拟和聚类多变量纵向轨迹提出新的统计模型.
- 解决分组纵向数据的复杂性,包括多模式和非典型观测.
- 扩展现有模型,以结合并发的共变量,提高灵活性.
主要方法:
- 开发了一种有限混合的多变体受污染的正常线性混合模型 (FM-MCNLMM).
- 引入了一个扩展版本 (EFM-MCNLMM),允许混合重量取决于共变量.
- 采用了交替期望条件最大化算法来进行最大概率估计.
主要成果:
- 拟议的FM-MCNLMM和EFM-MCNLMM模型有效处理多变量纵向数据.
- 通过全面的模拟来证明模型的实用性和有效性.
- 成功应用了该方法来分析阿尔茨海默病神经成像计划 (ADNI) 队列数据.
结论:
- 拟议的混合模型为分析复杂的分组纵向数据提供了强大的框架.
- 该方法为识别子组和了解疾病进展模式提供了有价值的工具.
- 这些模型在处理具有不同特征的数据方面是有效的,包括非典型的观测,正如ADNI数据分析所显示的那样.
相关概念视频
Multicompartment Models: Overview
497
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
497
Mechanistic Models: Compartment Models in Individual and Population Analysis
241
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...
241
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
282
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
282
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
238
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
238
Clearance Models: Noncompartmental Models
240
Clearance is a pharmacokinetic parameter traditionally defined by compartment models, signifying the rate at which a drug is expelled from the body. However, a noncompartmental model offers an alternative method for assessing clearance, primarily employing empirical data obtained after administering a single drug dose.
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
The noncompartmental approach capitalizes on extensive sampling data, correlating the volume of distribution to systemic exposure and the administered dosage. This method enables...
240
Multi-input and Multi-variable systems
384
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
In the absence of...
384


