一个混合效应模型,其中自相关错误结构的参数可以在个体之间不同
1Institut für Psychologie, University of Münster, Münster, Germany.
Multivariate behavioral research
|June 23, 2023
概括
这项研究将混合效应模型扩展到分析经验采样和日常日记方法的复杂心理数据. 改进的模型允许在剩余方差和自回归/移动平均线过程中进行随机效应,改进了纵向数据分析.
科学领域:
- 心理学 心理学 心理学
- 统计 统计 统计 统计
- 量化心理学 量化心理学
背景情况:
- 经验采样和日常日记方法在心理学研究中越来越多地被使用.
- 混合效应和多层模型是分析这些方法的纵向数据的标准.
研究的目的:
- 为心理学研究引入混合效应模型的扩展.
- 为了结合剩余方差和自回归/移动平均过程的随机效应.
- 为了提高复杂的纵向数据的分析.
主要方法:
- 描述了混合效果模型的扩展.
- 包括平均结构,余差和自回归/移动平均参数的随机效应.
- 使用适应高斯-赫米特方程和准蒙特卡洛集成的最大概率估计来近似复杂积分.
主要成果:
- 证明了扩展模型参数的估计.
- 插图模型应用程序与真实数据示例.
- 在模拟研究中比较了适应性高斯-赫米特二次方程和准蒙特卡洛集成.
结论:
- 扩展模型为分析心理数据提供了更灵活的框架.
- 拟议的整合方法为参数估计提供了可行的解决方案.
- 这项研究提升了复杂的纵向心理数据的分析能力.
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