Standard error estimates for rotated estimates of canonical correlation analysis: an implementation of the infinitesimal jackknife method

Autor: Jesse L. M. Wilkins, Hao Wu, Fei Gu, Yiu-Fai Yung
Rok vydání: 2021
Předmět:
Zdroj: Behaviormetrika. 48:143-168
ISSN: 1349-6964
0385-7417
DOI: 10.1007/s41237-020-00123-7
Popis: In applications of canonical correlation analysis (CCA), rotation of the canonical loadings is recommended to facilitate the interpretation of canonical variates. Based on the COSAN modeling approach to CCA proposed by Gu et al. (Multivar Behav Res 54:192–223, 2019), we describe the infinitesimal jackknife (IJ) method in modified COSAN-CCA models to obtain the IJ estimates of standard errors for rotated CCA estimates. Specifically, given two CCA rotation strategies (i.e., concurrent and separate) and two types of rotation method (i.e., orthogonal and oblique), our descriptions of the modified COSAN-CCA models and IJ method cover four rotation strategy-method combinations: concurrent-orthogonal, concurrent-oblique, separate-orthogonal, and separate-oblique. Simulation studies are used to evaluate the IJ estimates of standard errors, and a real data example is analyzed for illustration. We conclude that the IJ method is a trustworthy method for standard error estimation for rotated CCA estimates.
Databáze: OpenAIRE
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