A computer-assisted, K-fold cross-validation technique is discussed in the framework of canonical correlation analysis of randomly generated data sets. Analysis results suggest that this technique can effectively reduce the contamination of canonical variates and canonical correlations by sample-specific variance components. (Author/SLD)

Reviews methods for testing whether two or more correlation matrices differ from each other. Illustrates methods for evaluating the similarities of two independent correlation matrices, such as those obtained from boys and girls, and two dependent correlation matrices, such as those obtained in longitudinal research that uses multiple measures.…

Although stated objectives of multivariate multiple regression and canonical correlation seem different, aspects of the analyses themselves are mathematically equivalent. A numerical example of the similarities is given, with reference to omnibus significance testing, variable weighting schemes, and dimension reduction analysis. (SLD)

The purpose of the study was to investigate the relationship between college EFL students' autonomous learning capacity and motivation in using web-based Computer-Assisted Language Learning (CALL) in China. This study included three questionnaires: the student background questionnaire, the questionnaire on student autonomous learning capacity, and…

The primary purpose of this mixed-methods study was two-fold: first, to assess diabetes knowledge, attitudes, disease management and self efficacy among a sample of Mexican American (MA) and Mexican-Native (MN) adults living in North Texas; and second, to determine factors which promote or deter diabetes prevention and management using…

This paper introduces multilevel extensions for the general diagnostic model (GDM) following recent developments on extensions of latent class analysis (LCA) to hierarchical models. The GDM is based on LCA as well as discrete latent trait models and may be viewed as a general modeling framework for conrmatory multidimensional item response models.…

The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…

Student performance in basic math and reading skills in the United States trails behind other developed countries, providing the rationale for more research to determine how performance might be improved. Following evidence to conclude that multilingualism enhances cognitive, neuro-linguistic and meta-linguistic development, it is proposed that…

The impacts that the lack of physical cues and non-verbal cues of emotional expression has on the student learning experience in text based online environments were targeted separately in this study. A questionnaire was constructed with separate items for non-verbal cues of emotional expression and cues to physical identity. The survey also…

The present study prospectively investigated early temperamental profiles and their associations with autistic symptoms in high-risk infants (N = 138) with an older sibling with autistic spectrum disorder (ASD) and low-risk infants (N = 73) with no family history of ASD. Children who were diagnosed with ASD at 36 months were distinguished from…

The concept of the general linear model (GLM) is illustrated and how canonical correlation analysis is the GLM is explained, using a heuristic data set to demonstrate how canonical correlation analysis subsumes various multivariate and univariate methods. The paper shows how each of these analyses produces a synthetic variable, like the Yhat…

This paper illustrates how canonical correlation analysis can be employed to implement all the parametric tests that canonical methods subsume as special cases. The point is heuristic: all analyses are correlational, all apply weights to measured variables to create synthetic variables, and all yield effect sizes analogous to "r"…

Canonical analysis is frequently used in studies of relationships between sets of variables which are difficult to measure accurately, partly because of the true nature of the data and partly because of errors associated with the measurement instruments. Meredith's solution to the fallible data problem is examined. (Author/BJG)

The multivariate technique OVERALS is introduced as a non-linear generalization of canonical correlation analysis (CCA). First, two sets CCA is introduced. Two sets CCA is a technique that computes linear combinations of sets of variables that correlate in an optimal way. Two sets CCA is then expanded to generalized (or k sets) CCA. The…

Constructing scales on the basis of components analysis by assigning weights 1 to variables with high positive loadings on the components and -1 to variables with high negative loadings was compared with other strategies of scale construction, which assign weights 1 or -1 to variables with high weights for the components. (Author/BW)