在视觉世界范式中比较效果延迟:蒙特卡洛模拟来评估基于重新采样的程序
1UiT - The Arctic University of Norway, Stakkevollan, PO Box 6050, N-9037, Tromsø, Norway. sergey.minor@uit.co.
Behavior research methods
|February 23, 2026
概括
再抽样方法有效地将视觉世界范式 (VWP) 效应延迟与适当的样本大小进行比较. 变换测试和启动的置信区间提供高功率,而不会增加I型错误.
科学领域:
- 认知心理学 认知心理学
- 心理语言学 心理语言学
- 计算统计学 计算统计学
背景情况:
- 视觉世界范式 (VWP) 被广泛用于研究语言处理.
- 再抽样方法 (变换,启动) 是用于比较效果延迟的多功能方法,但需要验证.
- 之前的研究已经强调了在某些条件下这些方法的潜在失败.
研究的目的:
- 评估VWP效应延迟比较的基于重新采样的程序的统计能力和I型错误率.
- 为了比较各种延迟测量,包括新型效果大小值的排列和引导测试.
- 为在VWP研究中使用这些非参数方法提供基于证据的建议.
主要方法:
- 使用现有的VWP数据集进行蒙特卡洛模拟研究.
- 操纵的样本大小,真实效果大小,延迟测量和数据收集方法 (红外线与网络摄像头眼睛跟踪).
- 在五项研究中进行了156,000次模拟,分析了5.48亿个重新采样的数据集.
主要成果:
- 重新采样测试检测到延迟差异为200-300毫秒 (句子处理) 和100毫秒 (文字识别),样本大小足够.
- 变换测试和引导百分位置信区间显示出优越的功率和受控的I型错误率.
- 整合一个效果大小值会持续增加统计能力.
- 参与者重新抽样证明具有强大的跨主体变异性,与参与者内部引导不同.
结论:
- 当样本大小足够时,非参数重抽样方法对于VWP延迟比较是有效的.
- 建议进行变换测试和启动的CI,以控制它们的权力平衡和错误控制.
- 使用效果大小值可以提高延迟估计的统计能力.
- 仔细考虑重新抽样单元 (例如,参与者与参与者内部) 对于避免膨胀的I型错误率至关重要.
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