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Bacon, Donald R. – Multivariate Behavioral Research, 1995
A maximum likelihood approach to correlational outlier identification is introduced and compared to the Mahalanobis D squared and Comrey D statistics through Monte Carlo simulation. Identification performance depends on the nature of correlational outliers and the measure used, but the maximum likelihood approach is the most robust performance…
Descriptors: Comparative Analysis, Computer Simulation, Correlation, Estimation (Mathematics)