Abstract
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.
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The work reported in this paper has been supported by research grants from the Natural Sciences and Engineering Research Council of Canada to both authors. Requests for reprints should be sent to Yoshio Takane, Department of Psychology, 1205 Dr. Penfield Avenue, Montreal, QC, H3A 1B1, Canada.
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Takane, Y., Oshima-Takane, Y. Relationships Between two Methods for Dealing with Missing Data in Principal Component Analysis. Behaviormetrika 30, 145–154 (2003). https://doi.org/10.2333/bhmk.30.145
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DOI: https://doi.org/10.2333/bhmk.30.145