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相关概念视频

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

439
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...
439
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

33
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...
33
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

115
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,...
115
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

64
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...
64
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

105
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...
105
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

45
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...
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相关实验视频

Updated: Jun 16, 2025

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
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同时推断使用多个边际模型.

Ludwig A Hothorn1, Christian Ritz2, Frank Schaarschmidt3

  • 1Leibniz University Hannover, Hannover, Germany.

Pharmaceutical statistics
|August 21, 2024
PubMed
概括
此摘要是机器生成的。

本教程介绍了低维数据的同时推断,提供调整的p值和超出平均值比较的置信区间. 它利用相关性杆作用.

关键词:
克兰公司的CRAN包装.maxT-测试试验时间多个边际模型.同时推理推理的同时推理.

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相关实验视频

Last Updated: Jun 16, 2025

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08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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科学领域:

  • 生物统计学 生物统计学
  • 统计推理 统计推理
  • 多变量数据分析 多变量数据分析

背景情况:

  • 同时推断对于统计分析中的多重比较至关重要.
  • 现有的方法往往缺乏复杂的终点结构的调整p值和置信区间.
  • 对关联对统计测试的影响需要仔细考虑.

研究的目的:

  • 描述用于低维同时推断的单步方法.
  • 为各种比较提供调整的p值和置信区间.
  • 为了证明多重边际模型 (mmm) 方法的应用.

主要方法:

  • 利用对应关系对多变量t分布量的影响.
  • 通过多重边际模型 (mmm) 方法估计相关性矩阵.
  • 在使用R包的真实数据场景中使用mmm的maxT测试.

主要成果:

  • 该方法支持对不同尺度,相关的多个终点进行分析.
  • 它允许对相关的二进制终点进行联合分析.
  • 应用包括剂量建模,剂量/时间的联合测试,子组和各种回归模型.

结论:

  • 描述的同时推理方法是多功能和适用于复杂的数据结构.
  • 它为多个相关的终点提供了强大的统计推断.
  • 多重边际模型方法为先进的统计分析提供了灵活的框架.