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对等性测试来判断模型的合适性:蒙特卡洛模拟模拟
James L Peugh1, Kaylee Litson2, David F Feldon2
1Division of Behavioral Medicine and Clinical Psychology, Cincinnati Children's Hospital Medical Center.
Psychological methods
|August 10, 2023
概括
对于结构方程模型 (SEM) 匹配的等价性测试是不可靠的. 这次蒙特卡洛模拟发现RMSEA和CFI等效测试的性能不一致,特别是轻微的模型错误规范.
科学领域:
- 心理测量 心理测量 心理测量
- 统计建模 统计建模
- 量化心理学 量化心理学
背景情况:
- 传统的结构方程模型 (SEM) 适合像千平方,CFI和RMSEA这样的指数,表现不一致和不可靠.
- 研究人员缺乏可靠的推断替代方案来评估SEM合适性,经常依赖这些有问题的指数.
- 作为一个潜在的推断解决方案,建议RMSEA和CFI (RMSEA_eq,CFI_eq) 的等价性测试调整.
研究的目的:
- 实证地评估SEM适应指数 (RMSEA_eq,CFI_eq) 的同等性测试的准确性.
- 评估在各种条件下对等性测试的可靠性,包括样本大小,模型规格和数据特征.
- 为了确定同等性测试是否比传统方法更准确地判断可接受和不可接受的模型合适性.
主要方法:
- 采用了一个完全交叉的蒙特卡洛模拟.
- 在不同的条件下评估同等性测试的准确性:样本大小 (100-1,000),模型规范 (正确/错误规范),模型类型 (CFA,路径分析,SEM),变量负载,数据分布 (正常/扭曲) 和缺失数据 (0-25%).
- 使用比例z测试和逻辑回归来分析结果.
主要成果:
- 相当性测试表明,在各种独立变量条件下,性能不一致且不可靠.
- RMSEA_eq和CFI_eq的准确性通常取决于模拟条件之间的复杂相互作用.
- 发现SEM匹配的等价性测试存在问题,特别是在轻微的模型错误规格条件下.
结论:
- 目前对SEM适应指数 (RMSEA_eq,CFI_eq) 的同等性测试方法并不总是可靠的.
- 这些测试的有效性在很大程度上取决于特定的模型和数据特征,特别是错误规格.
- 研究人员在使用SEM适合性等效测试时应谨慎使用,直到进一步的研究和开发解决其局限性.
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