RELATIONSHIPS BETWEEN TWO METHODS FOR DEALING WITH MISSING DATA IN PRINCIPAL COMPONENT ANALYSIS

抄録

Missing data arise in virtually all practical data analysis situations. The problem of how to deal with them presents a major challenge to many data analysts. A variety of methods have been proposed to deal with missing data. In this paper we discuss two such proposals for principal component analysis (PCA) and investigate their mutual relationships. One was proposed by Shibayama (1988) for test equating (the TE method), and the other is called missing-data-passive (MDP) approach in homogeneity analysis (Meulman, 1982). The two methods are shown to be essentially equivalent despite their different guises.