Eskenazi, Michael A. "Best practices for cleaning eye movement data in reading research." Behavior Research Methods (2023): 1-11.
Finally, the outlier method is used to remove extreme data points that could bias the results. Outliers can occur for a variety of reasons, including experimenter or participant error, machine error, temporary lapse of attention, or other factors that result in data points that are not based on lexical processing. The typical method for removing outliers is to calculate the participant and condition-specific mean and standard deviation, and then to remove any fixation durations that are 2.5 or 3 standard deviations away from that mean.**** There are a variety of different methods for removing outliers, and researchers should be careful about which they choose (Berger & Kiefer, 2021). For example, when data have an ex-Gaussian distribution as with reaction time and fixation duration data, the typical outlier method results in trimming more data from the lower end than the higher end of the distribution (Miller, 1991).
Eskenazi, Michael A. "Best practices for cleaning eye movement data in reading research." Behavior Research Methods (2023): 1-11.
Finally, the outlier method is used to remove extreme data points that could bias the results. Outliers can occur for a variety of reasons, including experimenter or participant error, machine error, temporary lapse of attention, or other factors that result in data points that are not based on lexical processing. The typical method for removing outliers is to calculate the participant and condition-specific mean and standard deviation, and then to remove any fixation durations that are 2.5 or 3 standard deviations away from that mean.**** There are a variety of different methods for removing outliers, and researchers should be careful about which they choose (Berger & Kiefer, 2021). For example, when data have an ex-Gaussian distribution as with reaction time and fixation duration data, the typical outlier method results in trimming more data from the lower end than the higher end of the distribution (Miller, 1991).