Abstract
Hotelling’s canonical correlation is the Pearson product moment correlation between two weighted linear composites from two sets of variables. The two composites constitute a set of canonical variates, namely, a criterion variate and a predictor variate. Many statistical analyses in psychometrics deal with fallible data that contain measurement errors. A method of obtaining canonical correlations from the true-score covariance matrix is presented and contrasted with Meredith’s method for which the disattenuated canonical correlations are obtained from the correlation matrix of fallible data. Illustrations are presented with modified data from two seminal papers.
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Kim, SH. (2017). The Most Predictable Criterion with Fallible Data. In: van der Ark, L.A., Wiberg, M., Culpepper, S.A., Douglas, J.A., Wang, WC. (eds) Quantitative Psychology. IMPS 2016. Springer Proceedings in Mathematics & Statistics, vol 196. Springer, Cham. https://doi.org/10.1007/978-3-319-56294-0_11
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DOI: https://doi.org/10.1007/978-3-319-56294-0_11
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