We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

Background: There are minimal studies focusing on African American women and obesity, and there are even fewer studies examining obesity through a critical race theoretical framework. African American obesity research has largely focused on individual and community interventions, which have not been sufficient to reverse the obesity epidemic.…

Student-centered learning environments with upside-down pedagogies (SCALE-UP) are widely implemented at institutions across the country, and learning gains from these classrooms have been well documented. This study investigates the specific design feature(s) of the SCALE-UP classroom most conducive to teaching and learning. Using pilot survey…

The transition to adulthood and adulthood itself have been identified as times of stress for parents of individuals with autism spectrum disorder. Longitudinal studies, however, show improvements in the well-being of mothers of adolescents and young adults with autism spectrum disorder. This article presents a cross-sectional study of 102 Spanish…

Describes the strengths and weaknesses of a new type of multivariate technique, covariance structure analysis (LISREL). Provides a detailed example which shows how the use of covariance structure analysis can improve research sophistication and theory development in counseling psychology. (Author/ABB)

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)

Comments on Kerwin et al.'s article on covariance structure analysis (LISREL). Cautions that much effort must be made in developing the theory that describes the relationships among constructs and in establishing the measurement of these constructs before covariance structure is used. (ABB)

Canonical analysis of two convex polyhedral cones involves looking for two vectors whose square cosine is a maximum. New results about the properties of the optimal solution to this problem are presented. The convergence of an alternating least squares algorithm and properties of limits of calculated sequences are discussed. (SLD)

Several methods for dealing with incomplete multivariate data and ways to examine the effectiveness of these methods are discussed. It is concluded that pairwise and listwise deletions are among the least effective methods in terms of approximating the results, whereas estimates based on correlational procedures generally produce the most accurate…

The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…

Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)