对因子混合模型的应用进行系统的审查和反思
Eunsook Kim1, Yan Wang2, Hsien-Yuan Hsu3
1Department of Educational and Psychological Studies, University of South Florida.
因素混合模型 (FMM) 集成连续和分类变量. 这份对76项研究的综述考察了FMM的应用,挑战和心理研究的未来方向.
科学领域:
- 心理学科学 心理学科学
- 行为科学 行为科学
- 量化心理学 量化心理学
背景情况:
- 因子混合建模 (FMM) 结合了连续和分类潜变量.
- FMM允许同时对项目和观测进行集群.
- 两十年的FMM应用程序需要全面审查.
研究的目的:
- 系统地审查FMM在心理学和行为研究中的应用.
- 评估FMM的常见用途和实践.
- 确定应用研究人员面临的挑战,并提出改进建议.
主要方法:
- 进行了76个FMM应用程序的系统文献审查.
- 根据FMM方法论文献开发了一个全面的编码方案.
- 评估了常见实践,并确定了研究人员的挑战.
主要成果:
- 在应用研究中确定了FMM的普遍用途和实践.
- 突出了使用FMM的研究人员遇到的挑战和问题.
- 提供了在FMM应用程序中做出明智决策的实际建议.
结论:
- 在心理学和行为研究中,FMM是一个有价值的工具.
- 解决已识别的挑战可以加强FMM的实施.
- 未来的研究应该探索将FMM扩展到典型应用之外.
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