Moderated multiple regression (MMR) has become a fundamental tool for applied researchers, since many effects are expected to vary based on other variables. However, the inherent complexity of MMR creates formidable challenges for adequately performing power analysis on interaction effects to ensure reliable and replicable research results. Prior…

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…

This study was intended to establish whether self-esteem and study habits correlate with academic performance among university students. Research conducted was descriptive observational, multivariate or cross-sectional factorial in nature. The study population consisted of 196 students enrolled in a Basic Mathematics 1 class at the School of…

A common question asked by researchers using regression models is, What sample size is needed for my study? While there are formulae to estimate sample sizes, their assumptions are often not met in the collected data. A more realistic approach to sample size determination requires more information such as the model of interest, strength of the…

The study examined the prevailing assumption of education's role in labor market outcomes using samples from Korea's young adult population. KEEP, collected annually by KRIVET since 2004, includes an initial sample in 2004 of 12th graders from both general and vocational high schools; the sample size reflected a total of 2000 students for each…

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…

Purpose: Organisations invest heavily in training and development initiatives (Miller, 2012). However, a small percentage of what is learnt by the trainees from training gets transferred to the job (Mackay, 2007). The purpose of this study is to extend previous findings and examine various organisational factors, which have not been studied…

The selection and retention assessment process is dynamic. Dipboye, Smith, and Howell (1994) argued that the most influential portion of the final hiring process is the result of the interviewer's impression of the applicants. The Air Force Reserve Officer Training Corps program is responsible for selecting, retaining and ultimately hiring…

This study examined the intentions of educational leadership students in Florida university graduate programs in regards to demographics and self-assessed leadership characteristics. The study employed a non-experimental design wherein Regression, ANOVA, and Multiple Regression statistical techniques were employed to explore intent. It examined…

The purpose of this study was to explore the relation between primary grade teachers' knowledge of reading and reading instruction and a variety of educational, demographic, motivational, and self-perception variables. The sample for this study was comprised of 388 first, second, and third grade teachers. Data were obtained through the use of two…

Correlation matrices and standard deviations are the building blocks of many of the commonly conducted analyses in published research, and AERA and APA reporting standards recommend their inclusion when reporting research results. The authors argue that the inclusion of correlation/covariance matrices, standard deviations, and means can enhance…

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…

This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…

This study investigates the relationship between creative personality composition, innovative team climate, and team innovation based on an input-process-output model. We measured personality with the Creative Person Profile, team climate with the Team Climate Inventory, and team innovation through team-member and supervisor reports of team…

Structural equation modeling (SEM) refers to a family of statistical techniques that explores the relationships among a set of variables. Structural equation modeling provides an extremely versatile method to model very specific hypotheses involving systems of variables, both measured and unmeasured. Researchers can use SEM to study patterns of…