The Co-Varying Ties between Networks and Item Responses via Latent Variables.

IF 2.9 2区 心理学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Selena Wang, Tracy Morrison Sweet, Subhadeep Paul
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引用次数: 0

Abstract

Relationships among teachers are known to influence their teaching-related perceptions. We study whether and how teachers' advising relationships (networks) are related to their perceptions of satisfaction, students, and influence over educational policies, recorded as their responses to a questionnaire (item responses). We propose a novel joint model of network and item responses (JNIRM) with correlated latent variables to understand these co-varying ties. This methodology allows the analyst to test and interpret the dependence between a network and item responses. Using the JNIRM, we discover that teachers' advising relationships contribute to their perceptions of satisfaction and students more often than their perceptions of influence over educational policies. In addition, we observe that the complementarity principle applies in certain schools, where teachers tend to seek advice from those who are different from them. The JNIRM has the potential to improve the cost efficiency of network studies by integrating network and item response information during model estimation.

网络与项目反应之间的共变关系通过潜在变量。
众所周知,教师之间的关系会影响他们对教学的看法。我们研究了教师的咨询关系(网络)是否以及如何与他们对满意度、学生和对教育政策影响的看法相关,并记录为他们对问卷的回答(项目回答)。我们提出了一个具有相关潜在变量的网络和项目反应联合模型(JNIRM)来理解这些共变联系。这种方法允许分析人员测试和解释网络和项目响应之间的依赖关系。使用JNIRM,我们发现教师的建议关系比他们对教育政策影响的看法更有助于他们对满意度和学生的看法。此外,我们观察到互补原则适用于某些学校,那里的教师倾向于向与他们不同的人寻求建议。JNIRM有潜力通过在模型估计期间整合网络和项目响应信息来提高网络研究的成本效率。
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来源期刊
Psychometrika
Psychometrika 数学-数学跨学科应用
CiteScore
4.40
自引率
10.00%
发文量
72
审稿时长
>12 weeks
期刊介绍: The journal Psychometrika is devoted to the advancement of theory and methodology for behavioral data in psychology, education and the social and behavioral sciences generally. Its coverage is offered in two sections: Theory and Methods (T& M), and Application Reviews and Case Studies (ARCS). T&M articles present original research and reviews on the development of quantitative models, statistical methods, and mathematical techniques for evaluating data from psychology, the social and behavioral sciences and related fields. Application Reviews can be integrative, drawing together disparate methodologies for applications, or comparative and evaluative, discussing advantages and disadvantages of one or more methodologies in applications. Case Studies highlight methodology that deepens understanding of substantive phenomena through more informative data analysis, or more elegant data description.
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