A Note on the Asymptotic Aspect of the Treatment of Missing Values in Discriminant Analysis

Abstract

Abstract In an earlier article the authors studied five methods of handling missing values in discriminant analysis for small samples; this note points out the asymptotic behavior of these methods when the variables are equally correlated. The methods using either complete observation vectors or all sample values always attain the maximum probability of correct classification. Differences of the asymptotic probability of correct classification from its maximum are found to be small for all methods. Hence, comparison of the asymptotic bias seems to be of little practical importance and missing values in discriminant analysis must be studied for small samples.