我们应该如何模拟"变化"的影响 - - 或者我们应该?
Ethan M McCormick1, Daniel J Bauer2
1Methodology and Statistics Department, Institute of Psychology, Leiden University.
Psychological methods
|September 19, 2024
概括
研究人员警告不要在纵向模型中使用差异得分作为时间变化的共变量. 这种方法可能导致误导性结果,特别是在调解分析中,由于潜在的推断反转.
科学领域:
- 纵向数据分析的数据分析.
- 统计建模 统计建模
- 心理测量 心理测量 心理测量
背景情况:
- 关于纵向模型中的残留变化与差异得分存在争论.
- 以前的重点是对结果变量的变化建模.
- 这项研究将辩论扩展到纵向模型的共同变量方面.
研究的目的:
- 检查使用滞后与差异得分作为共变量所产生的问题.
- 为了推导不同时间变化的共变量表示的跨模型关系.
- 探索多变量纵向模型中调解分析的含义.
主要方法:
- 对纵向模型的关系系统的推导.
- 在应用的纵向设置中演示逻辑转换.
- 分析差异得分作为结果和预测因素.
主要成果:
- 当使用差异分数作为与结果相比的共变量时,也会出现类似的问题.
- 作为时间变化的共变量,差异得分可以诱导明显的推理反转.
- 对差异分数的影响的综合理解对于准确的分析至关重要.
结论:
- 建议在使用差异分数作为时间变化的协变量时谨慎使用.
- 使用差异分数可以导致误导性的统计推断.
- 对于有效的纵向研究来说,准确地表示时间变化的共变量是必不可少的.
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