Self-efficacy and mathematics anxiety have been identified as predictors of mathematics achievement. In the present study, secondary analyses on matrix summaries available from prior published studies were utilized to investigate the contribution that self-efficacy and mathematics anxiety made in mathematics performance. Commonality analyses were…

Conventional canonical methods distinguish between the two variable sets being analyzed, but the methods do not attempt to optimize the variance from a given variable set that will be contained in the final solution. In this respect canonical methods are said the be "symmetric." This paper proposes two non-symmetric, canonical-like…

Virtually all parametric statistical procedures have been shown to be special cases of canonical correlation analysis, which is a useful research methodology particularly when augmented by the calculation of canonical structure, index, and invariance coefficients. A logic for conducting stepwise canonical correlation analysis based upon evaluation…

Methods of regression commonality analysis are generalized for use in canonical correlation analysis. An actual data set (involving educators' attitudes toward death and age, locus of control, religion, and occupational role in working with terminally ill children) is employed to illustrate the extension. The method can be applied with respect to…

Data from 300 randomly selected K-12 teachers employed in 1979-80 in the Jefferson Parish (Louisiana) Public Schools revealed 10 predictor variables that substantially differentiated striking and nonstriking teachers. (Author/WD)

Multiple regression analysis is frequently being employed in experimental and non-experimental research. However, when data include predictor variables that are correlated, some regression results can become difficult to interpret. This paper presents a study to provide a demonstration that structure coefficients may be useful in these cases.…

Virtually all parametric statistical procedures have been shown to be special cases of canonical correlation analysis. This article proposes a logic for conducting stepwise canonical correlation analyses, based upon evaluation of canonical communality coefficients. The procedure is a direct analogue of stepwise multiple regression. (Author/RD)

Police officers (N=153) completed a self-report instrument measuring overt and covert anxiety, and a demographic survey exploring officers' perceptions of their need for counseling and to determine factors that predispose officers to seek counseling. Results indicated that officers would seek counseling if services were available. (RC)

The study investigated personality and aptitude correlates of test-wiseness skills, which were measured by assessing the subject's ability to utilize deductive reasoning and item cues. Personality factors and aptitude were measured. Results indicated that cognitive variables have more power to predict test-wiseness scores than do personality…

The importance of ascertaining and effectively treating psychological problems in children is difficult to overstate. Since compliance is particularly important, the psychological factors associated with caretakers' compliance regarding children's psychotherapy were examined here. Data were collected on the 85 primary caretakers of 85 children who…

Problems with using stepwise analytic methods are discussed, and better alternatives are illustrated. To make the illustrations concrete, an actual data set, involving responses of 91 medical school admissions directors to 30 variables, was used. The 30 variables involved perceptions of barriers to medical school with respect to characteristics of…

In early intervention, researchers often are interested in interpretation aids that can help determine the relative importance of variables when multiple regression models are used, and that facilitate deeper insight into prediction dynamics. Commonality analysis is one approach for helping researchers understand the contributions independent or…

The relationship between analysis of variance (ANOVA) methods and their analogs (analysis of covariance and multiple analyses of variance and covariance--collectively referred to as OVA methods) and the more general analytic case is explored. A small heuristic data set is used, with a hypothetical sample of 20 subjects, randomly assigned to five…