Sweating the Small Stuff: Does data cleaning and testing ... - Frontiers

FinchModern methods for the detection of multivariate outliersFIGURE 4 | Boxplots.datasets created by the various outlier detection methods, as wellas the full dataset. The strategy in this study was to remove allobservations that were identified as outliers by each method, thuscreating datasets for each approach that included only those notdeemed to be outliers. It is important to note that this is not typicallyrecommended practice, nor is it being suggested here. Rather,the purpose of this study was to demonstrate the impact of eachmethod on the data itself. Therefore, rather than take the approachof examining each outlier carefully to ascertain whether it was trulypart of the target population,the strategy was to remove those casesidentified as outliers prior to conducting statistical analyses. In thisway, it was hoped that the reader could clearly see the way in whicheach detection method worked and how this might impact resultinganalyses. In terms of the actual data analysis, the focus was ondescribing the resulting datasets. Therefore, distributional characteristicsof each variable within each method were calculated,including the mean, median, standard deviation, skewness, kurtosis,and first and third quartiles. In addition, distributions ofthe variables were examined using the boxplot. Finally, in orderto demonstrate the impact of these approaches on relational measures,Pearson’s correlation coefficient was estimated between eachpair of variables. All statistical analyses including identificationof outliers was carried out using the R software package, version2.12.1 (R Foundation for Statistical Computing, 2010). The R codeused to conduct these analyses appears in the Appendix at the endof the manuscript.RESULTSAn initial examination of the full dataset using boxplots appearsin Figure 4. It is clear that in particular the variable TIME-DRS is positively skewed with a number of fairly large values,even while the median is well under 10. Descriptive statistics forthe full dataset (Table 2) show that indeed, all of the variablesare fairly kurtotic, particularly TIMEDRS, which also displays astrong positive skew. Finally, the correlations among the threevariables for the full dataset appear in Table 3. All of thesewww.frontiersin.org July 2012 | Volume 3 | Article 211 | 65