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 approaches,
the maximum likelihood and the partitioned
maximum likelihood, are established based on the corresponding
multivariate polyserial and polychoric correlations.
A simulation study was conducted to compare
the various kinds of estimators.
Lee, Sik-Yum & Poon, Wai-Yin. (1987). Maximum likelihood estimation of multiple correlations and canonical correlations with categorical data. Applied Psychological Measurement, 11, 317-323. doi:10.1177/014662168701100309
Lee, Sik-Yum; Poon, Wai-Yin.
Maximum likelihood estimation of multiple correlations and canonical correlations with categorical data.
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