Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Regression Toward the Mean01:52

Regression Toward the Mean

6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

35
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
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...
47
Longitudinal Research02:20

Longitudinal Research

11.9K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.9K
Multiple Comparison Tests01:13

Multiple Comparison Tests

3.9K
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
3.9K
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

119
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
119

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Understanding Online Hate Toward Sexual and Gender Minorities: A Systematic Review.

Trauma, violence & abuse·2026
Same author

Regulatory Emotional Self-Efficacy and Hedonic Well-Being in Daily Life.

International journal of psychology : Journal international de psychologie·2025
Same author

Neurobehavioral disorders after severe acquired brain injury: Discrepancies between patients and caregivers' perception.

The Clinical neuropsychologist·2025
Same author

The Relations Among Prosocial Behavior, Life Satisfaction, and Hedonic Balance Among Young Adults.

Journal of personality·2025
Same author

Development and Validation of the Children's and Adolescents' Wellbeing at School Scale.

Scandinavian journal of psychology·2025
Same author

The Positive Effect of pro-Environmental Behavior on Eudaimonic Well-Being in Young Adults: A Daily Diary Study Using the Within-Person Encouragement Design.

Journal of personality·2025

相关实验视频

Updated: Jun 19, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K

应用研究的潜在变化得分模型:使用Mplus的实用指南.

Michele Vecchione1, Antonio Zuffianò2

  • 1Department of Social and Developmental Psychology, Sapienza University of Rome, Rome, Italy.

International journal of psychology : Journal international de psychologie
|July 24, 2024
PubMed
概括

本指南介绍了潜在变化得分 (LCS) 建模,用于分析随时间的变化. 它涵盖了基本和高级应用,包括变量之间的动态关系,为研究人员提供实用Mplus示例.

科学领域:

  • 心理学 心理学 心理学
  • 量化心理学 量化心理学
  • 统计建模 统计建模

背景情况:

  • 在许多科学学科中,分析随着时间的推移而发生的变化至关重要.
  • 结构方程建模 (SEM) 为此类分析提供了一个强大的框架.
  • 隐藏变化得分 (LCS) 在SEM中提供了一种灵活的方法,用于建模发展和动态过程.

研究的目的:

  • 为建模和解释隐性变化得分 (LCS) 模型提供实用指南.
  • 引入基本的LCS概念和扩展,包括双变化得分 (DCS) 模型.
  • 用Mplus软件展示使用施瓦茨基本个人价值观理论的应用程序.

主要方法:

  • 介绍基本的单变量潜变得分 (LCS) 模型.
  • 扩展到更复杂的模型:双变化得分 (DCS),比例变化和常量变化模型.
  • 应用双变量LCS模型来分析变量之间的动态关系.

主要成果:

  • 这篇文章说明了LCS模型如何有效地确定跨多个评估波的增长轨迹.
  • 两变量LCS模型被证明适用于模拟两个变量之间的动态相互作用.
  • 使用Mplus语法和输出的实用示例有助于实现和解释LCS模型.
关键词:
双变化得分是双变化得分.隐藏变化的变化.纵向研究是指纵向研究.个人价值观个人价值观.

更多相关视频

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.3K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.2K

相关实验视频

Last Updated: Jun 19, 2025

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

6.9K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.3K
Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
06:48

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

9.2K

结论:

  • 潜在变化得分 (LCS) 为分析纵向数据变化提供了一个强大而可适应的工具.
  • 本指南为学生,研究人员和从业人员提供了有效应用LCS模型的知识.
  • 施瓦茨的基本个人价值观理论的使用证明了LCS在心理学研究中的广泛适用性.