Abstract

In the present study Monte Carlo methods were employed to evaluate the degree to which canonical function and structure coefficients may be differentially sensitive to sampling error. Sampling error influences were investigated across variations in variable and sample (n) sizes, and across variations in average within-set correlation sizes and in across-set population correlation sizes. Sixty-four different research situations were investigated, and for each situation 1,000 random samples were drawn. Results suggest that both sets of coefficients are roughly equally influenced by sampling error, except perhaps when some intradomain correlation coefficients are quite large. Thus, the case for emphasizing interpretation of structure coefficients must be made on a psychometric basis, rather than on the grounds that structure coefficients are less sensitive to sampling error influences. (Eight data tables supplement the text. A scattergram of canonical composite scores, population parameters for 16 research situations, 64 tables of descriptive statistics each involving 1,000 samples, and two tables of mean deviations and mean absolute deviations from population values are appended.) (Author)

Citation

Thompson, B. Invariance on Multivariate Results: A Monte Carlo Study of Canonical Coefficients. Retrieved August 14, 2024 from https://www.learntechlib.org/p/140345/.

This record was imported from ERIC on March 21, 2014. [Original Record]

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Keywords

• Computer Simulation
• Correlation
• Monte Carlo Methods
• multivariate analysis
• Sampling
• Statistical Analysis
• Statistical Studies