Meta-analyses often include studies that report multiple effect sizes based on a common pool of subjects or that report effect sizes from several samples that were treated with very similar research protocols. The inclusion of such studies introduces dependence among the effect size estimates. When the number of studies is large, robust variance…

Several studies have stressed the importance of simultaneously estimating interaction and quadratic effects in multiple regression analyses, even if theory only suggests an interaction effect should be present. Specifically, past studies suggested that failing to simultaneously include quadratic effects when testing for interaction effects could…

Nursing programs across the United States (U.S.) rely upon simulation to complement or substitute for traditional clinical experiences. The purpose of this secondary analysis study is to use de-identified National Nursing Education Network (NNERN) (2015-2016) survey data of nursing students who participated in simulation to examine which selected…

Although literature about problem based learning (PBL) is not scarce, there is little research on experiences about learning methodologies that combine PBL and the use of simulation tools. This lack of studies is even more notable in the case of engineering courses. The motivation for this study is to show how such a combination of PBL and…

Simulated learning experiences using high-fidelity human patient simulators (HPS) are increasingly being integrated into baccalaureate nursing programs. Thus, the purpose of this study was to examine relationships among learning style, critical thinking disposition, critical thinking, and clinical judgment during high-fidelity human patient…

The underlying statistical models for multiple regression analysis are typically attributed to two types of modeling: fixed and random. The procedures for calculating power and sample size under the fixed regression models are well known. However, the literature on random regression models is limited and has been confined to the case of all…

P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…

The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable with "multiple" covariates. The performance of RTA is compared to the classical…

There are a variety of formulas for reducing the positive bias which occurs in estimating R squared in multiple regression or correlation equations. Five different formulas are evaluated in a Monte Carlo study, and recommendations are made. (JKS)

Several advantages to the use of factor scores as independent variables in a multiple regression equation were found. To help select the most desirable type of factor score on which to calculate a regression equation, computer-based Monte Carlo methods were used to compare the predictive accuracy upon replication of regression of five…

The major purpose of this study is to further the development of procedures which minimize current limitations of creativity instruments, thus yielding a reliable and functional means for assessing creativity. Computerized content analysis and multiple regression are employed to simulate the creativity ratings of trained judges. The computerized…

The intent of this document is to describe approximately 30 management science and organizational behavioral techniques with practical applications in school business management. Each technique is described by the mechanics of using the technique, specific applications of the technique, and requirements and constraints in the use of the technique.…