超越二分法:神经心理评估中的逻辑回归的一个例子
Robert J Spencer1,2, Sarah D Patrick1,2, Michael T Ransom1,2
1Mental Health Service, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Journal of clinical and experimental neuropsychology
|March 15, 2025
概括
使用切断分数对连续神经心理学数据进行二分类是有限的. 后勤回归 (LR) 为概率估计提供了一种优越的方法,改善了临床和研究决策.
科学领域:
- 神经心理学 神经心理学
- 统计 统计 统计 统计
- 心理测量 心理测量 心理测量
背景情况:
- 神经心理学家经常对决策的连续测试分数进行二分化.
- 这种做法虽然使传统的诊断统计成为可能,但却存在重大概念和统计方面的局限性.
研究的目的:
- 通过模拟的神经心理测试得分来探索与连续数据二分化相关的问题.
- 批判性地评估现有解决方案,并证明物流回归 (LR) 在克服这些局限性的实用性.
主要方法:
- 模拟了200名参与者的正常分布认知查测试数据.
- 查测试成绩和损伤指标之间的受约束相关性 (r=0.5).
- 计算了所有可能的切断分数的传统诊断统计数据和LR衍生的概率.
主要成果:
- 在曲线下的接收器操作特征面积为0.78,表明了足够的测试准确性.
- 通过截止分数解释数据会导致误导性分类 (对不同分数的类似处理,对相邻分数的分类区分).
- 多个切断分数加剧了这些分类问题.
结论:
- 倡导使用基于逻辑回归 (LR) 的概率估计,而不是基于组的截止分数,以从连续数据中做出二分法决策.
- 基于LR的概率利用了整个数据连续,避免了任意的切断选择,并提高了临床和研究应用中的准确性.
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