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相关概念视频

Survival Tree01:19

Survival Tree

75
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
75
Response Surface Methodology01:16

Response Surface Methodology

110
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
110
Cattell's 16 Personality Factors01:24

Cattell's 16 Personality Factors

593
Raymond Cattell's trait theory offers a structured framework for understanding personality by distinguishing between two critical traits: surface and source traits. Surface traits are observable patterns of behavior, such as indecisiveness, anxiety, and irrational fears. These traits are less stable, varying across situations and over time. This means that they are less helpful in understanding the deeper aspects of an individual's personality.
In contrast, source traits are the...
593
Self-Report Tests of Personality01:22

Self-Report Tests of Personality

336
Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
336
Trait Theory by Gordon Allport01:20

Trait Theory by Gordon Allport

596
Gordon Allport, often regarded as the father of American personality psychology, developed a theory that emphasized the importance of understanding people in their present lives rather than focusing on their past, as psychoanalysis did. Allport believed that personality should be studied in healthy, well-adjusted individuals rather than those with psychological problems. He was particularly interested in defining traits, which he saw as fundamental mental structures that guide behavior across...
596
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

177
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
177

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Author Spotlight: A Novel Setup to Conduct Naturalistic Laboratory Experiments with Real Human Actors in Scenarios
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对极端响应风格和基于特征的展开响应的项目响应树模型中的方向不变性进行调查.

Siqi He1, Justin L Kern1

  • 1University of Illinois at Urbana-Champaign, IL, USA.

Applied psychological measurement
|July 26, 2024
PubMed
概括

项目响应树 (IRT) 模型现在可以分析展开的响应,将协议和强度分开. 这种新方法允许在心理结构中进行定向不变性测试.

科学领域:

  • 心理测量 心理测量 心理测量
  • 项目响应理论.
  • 统计建模 统计建模

背景情况:

  • 项目响应树 (IRT) 模型通过分离协议和强度决策来提供细微分析.
  • 方向不变性至关重要,因为物品和人参数可能因协议方向而有所不同.

研究的目的:

  • 调查一个新的IRT模型家族,以展开反应.
  • 在协议和强度决策中纳入过度的共因数和分级响应模型.
  • 在这个框架内,检查项目和人级的方向不变性.

主要方法:

  • 开发了一系列IRT模型,整合了过度的共弦值和分级响应模型.
  • 通过JAGS进行了模拟研究,以评估参数恢复,使用贝叶斯方法.
  • 将模型应用于两个真实世界的数据集,比较具有不同方向不变性和过程假设的模型.

主要成果:

  • 拟议的IRT模型有效地处理展开的响应过程.
  • 通过模拟评估参数恢复,证明了模型的实用性.
  • 模型比较揭示了对方向不变和展开与主导过程的洞察力.

结论:

关键词:
贝叶斯估计贝叶斯估计在IRTree模型中,方向不变性是指向不变性的.响应方式 响应风格展开的模型可以展开.

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  • 新的IRT模型家族为分析展开的响应提供了一个强大的框架.
  • 这种方法有助于在心理测量中研究方向不变性.
  • 开发了可视化物件响应运作的方法,提高了可解释性.