Methods of Estimating Correlation Coefficients in the Presence of Influential Outlier(s)
Publication Date: 20/12/2021
Author(s): Etaga Harrison O., Okoro Ifeanyichukwu, Aforka Kenechukwu F., Ngonadi Lilian O..
Volume/Issue: Volume 4 , Issue 3 (2021)
Abstract:
Correlation methods are indispensable in the study of the linear relationship between two variables. However, many researchers often adopt inappropriate correlation methods in the study of linear relationships which usually leads to unreliable results. Recurrently, most researchers ignorantly employ the Pearson method in a dataset that contained outliers, instead of more appropriate correlation methods such as Spearman, Kendall Tau, Median and Quadrant which might be suitable in the calculation of correlation coefficient in the presence of influential outliers. It is noted that the accuracy of estimation of correlation coefficients under outliers has been a long-standing problem for methodological researchers. This is due to low knowledge of correlation methods and their assumptions which have led to inappropriate application of correlation methods in research analysis. Five different methods of estimating correlation coefficients in the presence of influential outlier (contaminated data) were considered: Pearson Correlation Coefficient, Spearman Correlation Coefficient, Kendall Tau Correlation Coefficient, Median Correlation Coefficient and Quadrant Correlation Coefficient.
Keywords:
Correction, Influential Outlier, Contaminated Data, Pearson, Spearman, Kendall, Quadrant
