Evaluation of the Degree of Separation between Two Data Populations with Statistical Algorithms
Final rept. Aug 2010-Apr 2011
ARMY EDGEWOOD CHEMICAL BIOLOGICAL CENTER APG MD RESEARCH AND TECHNOLOGY DIR
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This report investigates various existing statistical methods available in the literature and new statistical methods for evaluating the degree of separation between two peaks or two populations of data. The algorithms evaluated in this study include the direct percentage of overlap between the two populations of data, the Kolmogorov-Smirnov K-S test, the area between the receiver operating characteristic ROC curve and diagonal line, and the ROC curve length LROC. These algorithms are compared to the standard reference probability distribution for each data profile to be separated. Evaluations of the algorithms are presented in order to determine the relative degree of separation between the two peaks or distributions. The LROC is determined to provide the best estimation of the degree of separation compared to the other methods.
- Statistics and Probability