ScholarGate
助手

方法对比

并排查看您选择的方法;存在差异的行会高亮显示。

多层次量表开发×多层测量不变性×
领域心理测量学心理测量学
方法族Latent structureLatent structure
起源年份1990s–2000s2000s
提出者Raudenbush, Bryk, Hox and colleaguesMuthén, Asparouhov, and colleagues
类型Hierarchical measurement / scale constructionMeasurement model evaluation
开创性文献Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270. link ↗
别名multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale developmentMLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
相关53
摘要Multilevel scale development constructs and validates measurement instruments for data collected from individuals nested within higher-level units such as classrooms, organizations, or clinics. It partitions item variance into within-group and between-group components, ensuring that reliability and factor structure are evaluated at both levels simultaneously.Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research.
ScholarGate数据集
  1. v1
  2. 2 来源
  3. PUBLISHED
  1. v1
  2. 2 来源
  3. PUBLISHED

前往搜索 下载幻灯片

ScholarGate方法对比: Multilevel Scale Development · Multilevel Measurement Invariance. 于 2026-06-18 检索自 https://scholargate.app/zh/compare