Outliers in L2 Research in Applied Linguistics: A Synthesis and Data Re-Analysis
Outliers in L2 Research in Applied Linguistics: A Synthesis and Data Re-Analysis
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应用语言学二语研究中的异常值：综合和数据重新分析
DOI：
10.1017/s0267190520000057
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发表时间：
2020
影响因子：
3.7
通讯作者：
Luke Plonsky
中科院分区：
文献类型：
--
作者：
Christopher Nicklin;Luke Plonsky
摘要自定进度阅读（SPR）任务的数据通常会检查统计离群值（Marsden，Thompson和Plonsky，2018）。这样的数据点可以以各种方式处理（例如，修整、数据转换），其中每一个都可能以不同的方式影响研究结果。本研究分为两个阶段，首先，系统地回顾了涉及SPR的研究中发现的离群值处理技术，其次，重新分析SPR任务的原始数据，以了解这些技术的影响。为此，在第一阶段，收集了104项采用SPR任务的研究样本，并对不同的离群值处理进行编码。正如Marsden等人（2018年）所发现的那样，在确定合法阅读时间（RT）的时间选择和基于标准差（SD）的边界方面，整个样本中观察到了很大的差异。在II期，要求作者提供I期SPR研究的原始数据。获得了19个可用的数据集，并使用数据转换，SD边界，修剪和winsorizing重新分析，以测试其相对有效性归一化SPR反应时间数据。结果表明，在绝大多数情况下，对数转换规避了对SD边界的需要，这会盲目地消除或改变潜在的合法数据。结果还表明，SD边界的选择对数据的影响很小，并且在修剪和winsorizing之间没有显示有意义的差异，这意味着从SPR分析中盲目地去除数据可能是不必要的。为今后的研究提供了建议，涉及SPR数据和处理离群值在第二语言（L2）的研究更普遍。
Abstract Data from self-paced reading (SPR) tasks are routinely checked for statistical outliers (Marsden, Thompson, & Plonsky, 2018). Such data points can be handled in a variety of ways (e.g., trimming, data transformation), each of which may influence study results in a different manner. This two-phase study sought, first, to systematically review outlier handling techniques found in studies that involve SPR and, second, to re-analyze raw data from SPR tasks to understand the impact of those techniques. Toward these ends, in Phase I, a sample of 104 studies that employed SPR tasks was collected and coded for different outlier treatments. As found in Marsden et al. (2018), wide variability was observed across the sample in terms of selection of time and standard deviation (SD)-based boundaries for determining what constitutes a legitimate reading time (RT). In Phase II, the raw data from the SPR studies in Phase I were requested from the authors. Nineteen usable datasets were obtained and re-analyzed using data transformations, SD boundaries, trimming, and winsorizing, in order to test their relative effectiveness for normalizing SPR reaction time data. The results suggested that, in the vast majority of cases, logarithmic transformation circumvented the need for SD boundaries, which blindly eliminate or alter potentially legitimate data. The results also indicated that choice of SD boundary had little influence on the data and revealed no meaningful difference between trimming and winsorizing, implying that blindly removing data from SPR analyses might be unnecessary. Suggestions are provided for future research involving SPR data and the handling of outliers in second language (L2) research more generally.
影响因子：
4.3
作者：
Barr, Dale J.;Levy, Roger;Scheepers, Christoph;Tily, Harry J.
通讯作者：
Tily, Harry J.