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相关概念视频

Data Validation01:03

Data Validation

4.8K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
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Modeling in Therapy01:26

Modeling in Therapy

35
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
35
Formulating and Validating Nursing Diagnosis I01:26

Formulating and Validating Nursing Diagnosis I

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A nursing diagnosis is written when the nurse recognizes a cluster of essential patient data indicating health problems treated with independent nursing interventions. The standardized terminologies of a nursing diagnosis help nurses identify and treat patients' problems. Every electronic health record that uses nursing diagnosis must employ standard diagnostic terminology. Developing an efficient, individualized care plan begins with accurate nursing diagnoses.
There are thirteen domains...
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Formulating and Validating Nursing Diagnosis II01:25

Formulating and Validating Nursing Diagnosis II

2.5K
Nursing diagnoses represent a problem validated by major defining characteristics. There are four categories of nursing diagnoses: problem-focused, risk, health promotion or wellness, and syndrome. The anatomy of a nursing diagnosis includes three components: problem statement or diagnostic label, defining characteristics, and related factors.
Risk nursing diagnoses represent clinical judgments of an individual, family, or community more vulnerable to developing the health problem than others...
2.5K
Pedigree Analysis01:35

Pedigree Analysis

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Overview
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Beck's Cognitive Therapy01:25

Beck's Cognitive Therapy

27
Cognitive therapy is a psychological approach designed to address distortions in thinking, which can lead to negative emotions and unrealistic beliefs. These cognitive distortions often influence how individuals interpret and respond to situations, exacerbating emotional distress. Below are some prevalent cognitive distortions, their characteristics, and examples of how they manifest in thought processes.
Arbitrary Inference
Arbitrary inference involves making conclusions without sufficient...
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相关实验视频

Updated: May 15, 2025

Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
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Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

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在认知诊断模型中验证属性层次结构.

Xueqin Zhang1, Yu Jiang2, Tao Xin1

  • 1Collaborative Innovation Center of Assessment for Basic Education Quality, Beijing Normal University, Beijing, China.

Frontiers in psychology
|May 13, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了沃尔德统计学,用于测试认知诊断模型 (CDM) 中的属性层次结构. 沃尔德-XPD方法证明了有效的性能和效率,为属性层次验证提供了可靠的方法.

关键词:
属性层次结构属性层次结构.认知诊断模型是一种认知诊断模型.一个共变矩阵.信息矩阵是一个信息矩阵.概率比率测试的可能性比率测试.

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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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科学领域:

  • 心理测量 心理测量 心理测量
  • 教育测量教育的测量
  • 隐性变量建模 隐性变量建模

背景情况:

  • 认知诊断模型 (CDM) 对于理解受试者属性掌握至关重要.
  • 属性层次是CDM的关键结构特征,提供了关键的见解.
  • 对于属性层次结构的现有概率比 (LR) 测试面临非标准非对称分布的挑战,导致测试失败.

研究的目的:

  • 提出和评估沃尔德统计作为一种新的方法,用于统计测试CDM中先行定义的属性层次结构.
  • 为了比较两个沃尔德统计变异的性能,沃尔德-XPD和沃尔德-Obs,使用不同的协差矩阵估计器.

主要方法:

  • 该研究介绍了Wald统计用于CDM中的属性层次测试.
  • 使用了两种协差矩阵估计器,即实证交叉产品 (XPD) 和观察到的信息 (Obs).
  • 进行了模拟研究,以评估Wald-XPD和Wald-Obs在各种条件下的性能.

主要成果:

  • 沃尔德-XPD统计表明,在不同项目的质量方面,可以接受的经验性表现.
  • 与其他方法相比,Wald-XPD表现出更高的测试效率.
  • 拟议的方法用真实世界的数据集来说明.

结论:

  • 沃尔德统计,特别是沃尔德-XPD,为验证CDM中的属性层次提供了可行和高效的替代方案.
  • 这种方法解决了现有的LR测试的局限性,在属性层次评估中提供了更高的可靠性.
  • 这些发现支持Wald-XPD方法在教育和心理测量环境中的实用性.