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相关概念视频

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

47
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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Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

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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...
35
SFG Algebra01:16

SFG Algebra

114
In Signal Flow Graph (SFG) algebra, the value a node represents is determined by the sum of all signals entering that node. This summed value is then transmitted through every branch leaving the node, making the SFG a powerful tool for visualizing and analyzing control systems.
Each node in an SFG corresponds to a variable, and the interactions between nodes are represented by branches with associated gains. When multiple branches lead into a node, the value at that node is the sum of the...
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Linear Circuits01:17

Linear Circuits

393
A linear circuit is characterized by its output having a direct proportionality to its input, adhering to the linearity property, which encompasses the principles of homogeneity (scaling) and additivity. Homogeneity dictates that when the input, also referred to as the excitation, is multiplied by a constant factor, the output, known as the response, is correspondingly scaled by the same constant factor. For instance, if the current is multiplied by a constant 'k,' the voltage likewise...
393
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

88
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
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State Space Representation01:27

State Space Representation

185
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
185

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功能分析的通用线性混合效应建模 (GLMM) 图形构建元素在视觉分析上.

Art Dowdy1, Kasey Prime1, Corey Peltier2

  • 1Department of Teaching and Learning, College of Education and Human Development, Temple University, Philadelphia, PA USA.

Perspectives on behavior science
|August 5, 2024
PubMed
概括

功能分析中的图形操作可能会影响数据的解释. 董事会认证的行为分析师与视觉检查标准的一致性很低,突出了应用行为分析中需要改进的分析方法的需要.

关键词:
这就是DPPXYRR.功能分析是一种功能分析.在 GLMMM 里面.图形的构造 图形的构造多元件设计多元件设计开放科学是一个开放的科学.视觉分析 视觉分析

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科学领域:

  • 应用行为分析 (ABA)
  • 实验设计 实验设计
  • 数据可视化 数据可视化

背景情况:

  • 多元件设计对于在ABA中评估功能分析结果至关重要.
  • 准确的数据收集,图形和视觉分析对于有效的干预决策至关重要.
  • 时间序列图和视觉分析是解释功能分析数据的标准方法.

研究的目的:

  • 评估图形构造中的x-y轴比 (DPPXYR) 是否影响多元件设计中功能关系的检测.
  • 评估通过董事会认证的行为分析师 (BCBA) 进行的视觉分析与修改的视觉检查 (MVI) 标准之间的一致性.

主要方法:

  • 来自功能分析的32个多元件设计图被用来测试DPPXYR操纵对视觉分析师检测功能的影响.
  • 59个BCBA对数据集进行了视觉分析,并将他们的决定与MVI标准进行了比较.
  • 使用统计建模 (交叉GLMM) 来确定数据的最佳分析方法.

主要成果:

  • DPPXYR的图形结构操纵影响了功能关系的检测.
  • 在测试数据集中,BCBAs的视觉分析决策与MVI标准之间观察到很少的对齐.
  • 确定的最佳统计模型是一个交叉的GLMM,随机的斜率和拦截,不包括相互作用效应.

结论:

  • 图形呈现特征,如DPPXYR,可以显著影响功能分析数据的解释.
  • 在BCBA如何视觉分析功能分析数据和建立MVI标准之间存在显著的差异,这表明解释中的潜在不一致性.
  • 该研究强调了透明的数据分析和在应用行为分析中遵守标准化的视觉检查方法的重要性.