拉什模型
心理学
结构方程建模
多向拉希模型
验证性因素分析
结构效度
可靠性(半导体)
比例(比率)
面(心理学)
心理测量学
优势和劣势
构造(python库)
路径分析(统计学)
应用心理学
社会心理学
项目反应理论
统计
计算机科学
发展心理学
数学
五大性格特征
功率(物理)
物理
人格
量子力学
程序设计语言
作者
Kenneth Leithwood,Jingping Sun,Randall E. Schumacker,Hua Cheng
出处
期刊:Journal of Educational Administration
[Emerald (MCB UP)]
日期:2023-04-07
卷期号:61 (4): 385-404
被引量:3
标识
DOI:10.1108/jea-08-2022-0115
摘要
Purpose This study extends research on one of the most frequently cited school leadership frameworks by examining the psychometric properties of the instrument designed to assess many of the practices included in that framework. Design/methodology/approach Using data collected from 1,401 teachers the study examined the instrument’s measurement invariance, score reliabilities, as well as construct and predictive validities. Polytomous latent trait models (Many-Facet Rasch model), scale and principal component analysis using second-order Confirmatory Factor Analysis, and Structural Equation Modeling (SEM)-Path modelling were used for these purposes. Findings Findings report levels of score reliability and valid score inferences. Results concerning the predictive validity of the instrument indicate a complex set of relations among the domains of leadership practices measured by the instrument, variables selected as mediators of leaders’ influence, and their direct and indirect effects on student learning. Research limitations/implications This study provides researchers with a reliable and valid instrument for use in their future research. Data for the study were provided by elementary teachers in one US state. The extent to which results of the instrument are valid across different cultural and organizational settings remains to be determined. Practical implications Leadership developers may find the instrument useful for assessing the strengths and weaknesses of those participating in their programs while leaders themselves many find the instrument useful for self-diagnosis. Originality/value This study contributes to the development of school leadership measures by including Rasch modeling among the methods used for examining the instrument’s psychometric properties.
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