Background: Rooted in problems of social justice, intersectionality addresses intragroup differences in impacts and outcomes and the compound discrimination at specific intersections of classification (Crenshaw,1991). It stresses that deficits/debts in outcomes often occur non-additively; for example, discriminatory hiring practices can be…

Percentage of uncontaminated correlations (PUC), explained common variance (ECV), and omega hierarchical ([omega]H) have been used to assess the degree to which a scale is essentially unidimensional and to predict structural coefficient bias when a unidimensional measurement model is fit to multidimensional data. The usefulness of these indices…

Regression factor score predictors have the maximum factor score determinacy, that is, the maximum correlation with the corresponding factor, but they do not have the same inter-correlations as the factors. As it might be useful to compute factor score predictors that have the same inter-correlations as the factors, correlation-preserving factor…

In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different…

When performing regression analysis, one way to examine the normality of data is to screen outliers. Outliers, on the other hand, do not always have an effect on regression results. In reality, cases with a large amount of residuals that affect regression analysis results are referred to as influential cases. It is important to detect them in the…

Linear functional relationships are intended to be symmetric and therefore cannot generally be accurately estimated using ordinary least squares regression equations. Orthogonal regression (OR) models allow for errors in both "Y" and "X" and therefore can provide symmetric estimates of these relationships. The most…

Previous research has suggested mixed results concerning gifted populations and achievement goal orientation. This study investigated achievement goal orientation in honors and general education undergraduate students, exploring the factor structure of a commonly used assessment and looking at ability level differences using two types of…

This study examined the nexus between institutional training and development and employee performance from private universities in Ghana using Principal Components Regression (PCR). The study employed exploratory design through the quantitative and cross-sectional survey methods for data collection. The questionnaires were administered 384…

Ordinary least squares (OLS) regression provides optimal linear predictions of a dependent variable, y, given an independent variable, x, but OLS regressions are not symmetric or reversible. In order to get optimal linear predictions of x given y, a separate OLS regression in that direction would be needed. This report provides a least squares…

Factor score regression (FSR) is widely used as a convenient alternative to traditional structural equation modeling (SEM) for assessing structural relations between latent variables. But when latent variables are simply replaced by factor scores, biases in the structural parameter estimates often have to be corrected, due to the measurement error…

A large body of work has shown that science teacher knowledge is one of the most fundamental components of effective teaching and learning. Our study analyzes the Praxis® Earth and Space Science Content Knowledge Test (ESS CKT) from May 2006 to June 2016. We present one of the largest datasets comprising 11,273 ESS teacher candidates in order to…

Ordinary least squares (OLS) regression and orthogonal regression (OR) address different questions and make different assumptions about errors. The OLS regression of Y on X yields predictions of a dependent variable (Y) contingent on an independent variable (X) and minimizes the sum of squared errors of prediction. It assumes that the independent…

Purpose: The paper focuses on exploring the influence of structural and functional characteristics of demonstrations on their effectiveness. Design/Methodology: In the framework of AgriDemo-F2F project, we analysed the responses to 345 post-demonstration questionnaires filled out by the attendees of 31 demo events held in 12 EU countries. Factor…

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…

This study with 850 students examined the interrelations of students' own and perceived teacher reference norms in combination with estimating the relations of these constructs to self-concept in the domain of mathematics. All reference norms were positively interrelated. Regression models yielded different results across school tracks: In…