Department of Psychological and Quantitative Foundations, University of Iowa.
Psychol Methods. 2018 Mar;23(1):1-26. doi: 10.1037/met0000107. Epub 2017 Jan 23.
Although widely recognized as a comprehensive framework for representing score reliability, generalizability theory (G-theory), despite its potential benefits, has been used sparingly in reporting of results for measures of individual differences. In this article, we highlight many valuable ways that G-theory can be used to quantify, evaluate, and improve psychometric properties of scores. Our illustrations encompass assessment of overall reliability, percentages of score variation accounted for by individual sources of measurement error, dependability of cut-scores for decision making, estimation of reliability and dependability for changes made to measurement procedures, disattenuation of validity coefficients for measurement error, and linkages of G-theory with classical test theory and structural equation modeling. We also identify computer packages for performing G-theory analyses, most of which can be obtained free of charge, and describe how they compare with regard to data input requirements, ease of use, complexity of designs supported, and output produced. (PsycINFO Database Record
尽管被广泛认为是一种用于表示评分可靠性的综合框架，但广义理论（G 理论）尽管具有潜在的益处，但在报告个体差异测量结果时很少被使用。在本文中，我们强调了 G 理论在量化、评估和改善评分心理测量特性方面的许多有价值的方法。我们的示例涵盖了整体可靠性的评估、由测量误差的个别来源所解释的分数变异百分比、决策时的评分截距的可靠性、对测量程序变更的可靠性和依赖程度的估计、对测量误差的效度系数的衰减以及 G 理论与经典测试理论和结构方程模型的联系。我们还确定了用于进行 G 理论分析的计算机软件包，其中大多数都可以免费获得，并描述了它们在数据输入要求、易用性、支持的设计复杂性以及生成的输出方面的比较。
