Abstract

We used structural equation modeling techniques to expand traditional generalizability theory (G-theory) models to allow for congeneric relationships among item responses while accounting for the primary sources of measurement error that affect results from objectively scored, self-report measures. Data came from 919 respondents who completed the Agreeableness, Conscientiousness, Extraversion, Neuroticism, and Openness subscales of the Big Five Inventory (BFI; John et al., 1991 John, O. P., Donahue, E. M., & Kentle, R. L. (1991). The Big Five Inventory – Versions 4a and 54. University of California, Berkeley, Institute of Personality and Social Research. [Google Scholar]) on two occasions. When compared to traditional and factor-based essential tau-equivalent G-theory models, congeneric models on average yielded superior fit statistics, higher estimates of reliability, and lower estimates of transient and specific-factor measurement error. Essential tau-equivalent and congeneric factor models also were configured to allow for simultaneous partitioning of systematic and measurement error variance at both total score and individual item levels. We provide detailed guidelines, examples, and computer code in R for all models discussed in an extended online supplement to enable readers to apply the demonstrated techniques.

摘要

我们使用结构方程建模技术来扩展传统的泛化理论 (G 理论) 模型，以考虑项目响应之间的同类关系，同时考虑影响客观评分、自我报告测量结果的测量误差的主要来源。数据来自 919 名完成了大五清单 (BFI; John et al., 1991)的宜人性、尽责性、外向性、神经质和开放性分量表的受访者 John, OP , Donahue, EM , & Kentle, RL ( 1991 )。大五清单 - 版本 4a 和 54。加州大学伯克利分校人格与社会研究所。 [Google Scholar] ) 两次。与传统的和基于因子的基本 tau 等效 G 理论模型相比，同类模型平均产生了卓越的拟合统计、更高的可靠性估计以及更低的瞬态和特定因子测量误差估计。基本的 tau 等效和同类因子模型也被配置为允许在总分和单个项目级别同时划分系统和测量误差方差。我们为扩展的在线补充中讨论的所有模型提供了 R 语言中的详细指南、示例和计算机代码，以使读者能够应用演示的技术。