分层分布分析 - - 一个关于RT分布的新视角
Rüdiger Thul1, Joseph Marsh1, Ton Dijkstra2
1School of Mathematical Sciences, University of Nottingham, Nottingham, UK.
概括
分层分布分析 (SDA) 揭示了单词频率和长度如何影响响应时间分布. 语境多样性最好地预测了大词汇数据集中响应时间的逻辑正常分布.
科学领域:
- 认知心理学 认知心理学
- 计算语言学 计算语言学
- 心理语言学 心理语言学
背景情况:
- 响应时间 (RT) 和它们的分布为认知过程提供了洞察力.
- 了解词的特性,如频率和长度如何影响RT分布,对于认知理论至关重要.
- 现有的方法可能无法完全捕捉到单词特征和RT变异性之间的复杂关系.
研究的目的:
- 引入一种新的统计方法,分层分布分析 (SDA),用于定量评估响应时间分布的决定因素.
- 通过使用大规模的词汇决策数据,研究单词频率和长度对响应时间分布的影响.
- 确定最佳的概率分布和单词发生量,用于建模响应时间分布.
主要方法:
- 将分层分布分析 (SDA) 应用于来自英语和英国词典项目的数百万个词典决策响应时间.
- 分析了响应时间分布作为单词频率和单词长度的函数.
- 比较了lognormal,Wald和gamma分布,并评估了词形频率,话语上下文多样性和用户上下文多样性.
主要成果:
- 响应时间分布最好用lognormal分布来描述,当使用上下文多样性措施量化单词出现时.
- 使用层次化的贝叶斯框架,SDA为分布参数提供了参与者级别的后向分布.
- 该方法允许基于单词频率和长度对响应时间进行概率预测.
结论:
- 分层分布式分析 (SDA) 通过合适的概率分布有效阐明了控制响应时间生成的机制.
- 这些发现凸显了文本处理模型中的上下文多样性测量的实用性.
- SDA是一种多功能工具,适用于除了词汇决策之外的各种认知任务,包括单词命名和眼睛跟踪.
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