一个解释性的多维随机项目影响评级规模模型
Sijia Huang1, Jinwen Jevan Luo2, Li Cai2
1Indiana University Bloomington, USA.
Educational and psychological measurement
|November 17, 2023
概括
本研究引入了一种新的多维随机项目效应评级规模模型,用于项目响应理论 (IRT). 该模型有效地结合了共变量,并使用一种新的算法证明了准确的参数恢复.
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
- 统计建模 统计建模
背景情况:
- 随机物品效应物品响应理论 (IRT) 模型越来越多地被使用.
- 这些模型在实际应用中提供了优势,因为它们将人体和物体效应都视为随机.
- 现有的模型可能缺乏灵活性来结合共变量信息.
研究的目的:
- 引入一个解释性的多维随机项目效应评级尺度模型.
- 允许灵活纳入与人和物品相关的共变量,以分析它们对潜在变量的影响.
- 介绍名义响应模型 (NRM) 的新型参数化.
主要方法:
- 开发了一个多维的随机项目效应评级规模模型.
- 使用名义响应模型 (NRM) 的新参数化来制定模型.
- 采用了Metropolis-Hastings-Robbins-Monro (MH-RM) 算法的新变体,用于在具有交叉随机效应的潜在变量模型中进行参数估计.
主要成果:
- 拟议的模型展示了灵活包括人与物品相关的共变量的能力.
- 新的MH-RM算法在参数估计方面表现良好.
- 模拟研究表明,模型参数得到了很好的恢复.
结论:
- 拟议的多维随机项目效应评级规模模型为分析复杂数据提供了灵活的框架.
- 开发的MH-RM算法在此类模型中有效估计参数.
- 该模型和算法适用于现实世界的经验数据分析.
更多相关视频
09:00Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
Published on: August 16, 2024
792
10:58Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
Published on: August 28, 2021
4.5K
相关概念视频
Self-Report Tests of Personality
357
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.
357
Factorial Design
13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Response Surface Methodology
141
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:
The process of RSM involves several key steps:
141
Multiple Regression
3.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.0K
Personality Theory by Eysenck and Eysenck
476
Hans and Sybil Eysenck developed a widely recognized theory of personality, which emphasizes the role of temperament and genetically based differences in shaping individual traits. Their theory posits that biological factors primarily determine personality and can be understood through two main dimensions: extroversion/introversion and neuroticism/stability.
In the extroversion/introversion dimension, highly extroverted people are sociable, outgoing, and easily connect with others. In contrast,...
In the extroversion/introversion dimension, highly extroverted people are sociable, outgoing, and easily connect with others. In contrast,...
476
Group Design
8.9K
The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
8.9K
