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Maximum Likelihood Estimation of Multiple Correlations and Canonical Correlations with Categorical Data

The Chinese University of Hong Kong

Wal-Yin Poon

University of California, Los Angeles

In the behavioral and social sciences, investigators frequently encounter latent continuous variables which are observable only in polytomous form. This paper considers the estimation of multiple correlations and canonical correlations for these variables. Two ap proaches, the maximum likelihood and the partitioned maximum likelihood, are established based on the cor responding multivariate polyserial and polychoric cor relations. A simulation study was conducted to com pare the various kinds of estimators.

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