Accommodating and Extending Various Models for Special Effects Within the Generalized Partially Confirmatory Factor Analysis Framework

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Yifan Zhang, Jinsong Chen
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引用次数: 0

Abstract

Special measurement effects including the method and testlet effects are common issues in educational and psychological measurement. They are typically covered by various bifactor models or models for the multiple traits multiple methods (MTMM) structure for continuous data and by various testlet effect models for categorical data. However, existing models have some limitations in accommodating different type of effects. With slight modification, the generalized partially confirmatory factor analysis (GPCFA) framework can flexibly accommodate special effects for continuous and categorical cases with added benefits. Various bifactor, MTMM and testlet effect models can be linked to different variants of the revised GPCFA model. Compared to existing approaches, GPCFA offers multidimensionality for both the general and effect factors (or traits) and can address local dependence, mixed-type formats, and missingness jointly. Moreover, the partially confirmatory approach allows for regularization of the loading patterns, resulting in a simpler structure in both the general and special parts. We also provide a subroutine to compute the equivalent effect size. Simulation studies and real-data examples are used to demonstrate the performance and usefulness of the proposed approach under different situations.
在广义部分确认因素分析框架内适应和扩展各种特殊效果模型
包括方法效应和小测验效应在内的特殊测量效应是教育和心理测量中的常见问题。对于连续数据,通常有各种双因子模型或多特征多方法(MTMM)结构模型;对于分类数据,则有各种小测验效应模型。然而,现有模型在适应不同类型效应方面存在一些局限性。广义部分确证因子分析(GPCFA)框架稍加修改,就能灵活地适应连续和分类情况下的特殊效应,并带来更多好处。各种双因子、MTMM 和 testlet 效应模型都可以与修订后的 GPCFA 模型的不同变体相联系。与现有方法相比,GPCFA 提供了一般因素和效应因素(或特质)的多维性,并能共同解决局部依赖性、混合型格式和缺失问题。此外,部分确认法允许对载荷模式进行正则化,从而使一般和特殊部分的结构更加简单。我们还提供了一个计算等效效应大小的子程序。我们使用模拟研究和真实数据示例来证明所提方法在不同情况下的性能和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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