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Updated: Jun 18, 2025

An Air-liquid Interface Bronchial Epithelial Model for Realistic, Repeated Inhalation Exposure to Airborne Particles for Toxicity Testing
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暴露混合物的功率分析 通过蒙特卡洛模拟的暴露混合研究

Phuc H Nguyen1, Amy H Herring1, Stephanie M Engel2

  • 1Department of Statistical Science, Duke University, Durham, 27710, NC, USA.

Statistics in biosciences
|August 2, 2024
PubMed
概括

研究人员现在可以很容易地估计样本大小和环境暴露混合研究的统计能力,使用新的R包,mpower. 该工具简化了复杂的模拟,用于先进的流行病学方法.

关键词:
蒙特卡洛模拟的蒙特卡洛模拟在R包中,R包是R包.环境化学混合物 环境化学混合物观察性研究是一种观察性研究.动力分析分析能力分析

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Mechanistic Models: Compartment Models in Individual and Population Analysis

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...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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.
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