在统计介导分析中估计潜在的基线-治疗相互作用
Oscar Gonzalez1, Jeno R Millechek1, A R Georgeson2
1University of North Carolina at Chapel Hill.
概括
这项研究解决了统计中介分析的挑战,提供了估计基线治疗相互作用 (BTI) 影响与潜在变量的方法. 它为使用结构模型或潜变量评分的研究人员提供了实际指导.
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:
- 统计调解分析确定了解释治疗对结果影响的调解者.
- 根据基线变量进行调节是常见的,但估计基线治疗相互作用 (BTI) 与潜在变量的影响是具有挑战性的.
- 现有的方法缺乏指导,用于中介中隐藏的BTI估计.
研究的目的:
- 在调解分析中提供和评估估计潜在基线-通过-治疗相互作用 (BTI) 效应的方法.
- 为了解决在BTI估计中处理潜在变量的指导需求.
- 为分析复杂调解模型的研究人员提供实用解决方案.
主要方法:
- 讨论了两种一般方法:结构模型和在观察到BTI估计之前的潜在变量评分.
- 使用模拟研究来评估偏差,功率,1型错误率和间隔覆盖率.
- 插图方法与一个应用的例子,并提供了R和Mplus语法.
主要成果:
- 模拟结果详细说明了用于估计潜伏BTI和介导效应的拟议方法的性能.
- 评估偏差,统计能力,1型错误率和信任区间覆盖范围.
- 通过一个应用的例子证明了方法的实际实用性.
结论:
- 这项研究提供了可行的方法来估计中介分析中的潜在BTI效应.
- 为研究人员提供工具和指导,以便更准确地进行涉及潜在变量的调解分析.
- 促进在心理学研究中实施先进的调解模型.
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