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There is a growing awareness in methodological literature that parametric statistical tests may not be appropriate in studies with a small sample size and non-normal data (Larson-Hall and Herrington 2010; Mizumoto and Plonsky 2016). In addition, the presence of outliers or cases widely different from the rest of the data set poses serious methodological challenges: even a single extreme case can invalidate the estimated statistics in parametric methods (Larson-Hall and Herrington 2010). As Larson-Hall (2010) noted, removing outliers from the data set is undesirable for several reasons. First, such decisions are based on the researcher’s subjective opinion. Secondly, when one outlier is removed another may emerge and the subsequent removal of all outlying cases could drastically reduce the number...
