Lenhard and Lenhard (2021) investigate how regression-based continuous norming can enhance the quality of norm scores in psychometric testing. Their study compares semiparametric continuous norming (SPCN) with conventional methods, evaluating performance across a wide range of simulated test conditions and sample sizes. Background Norm scores are crucial in psychological and …
The article by Coelho, Hanel, and Wolf (2018) presents the NCS-6, a shortened version of the Need for Cognition Scale (NCS-18). This scale measures an individual’s tendency to engage in and enjoy thinking, a concept that has become significant in fields like social and medical sciences. By reducing the original …
Liang’s (2020) study on Bayesian Structural Equation Modeling (BSEM) focuses on the use of small-variance normal distribution priors (BSEM-N) for analyzing sparse factor loading structures. This research provides insights into how different priors affect model performance, offering valuable guidance for researchers employing BSEM in their work. Background Bayesian Structural Equation …
The study by Xiao and Bulut (2020) evaluates how different methods for handling missing data perform when estimating ability parameters from sparse datasets. Using two Monte Carlo simulations, the research highlights the strengths and limitations of four approaches, providing valuable insights for researchers and practitioners in educational and psychological measurement. …
Olvera Astivia, Kroc, and Zumbo’s (2020) study examines the assumptions underlying Cronbach’s coefficient alpha and how the distribution of items affects reliability estimation. By introducing a new framework rooted in Fréchet-Hoeffding bounds, the authors offer a fresh perspective on the limitations of this widely used reliability measure. Their work provides …
Determining the optimal number of factors to retain in exploratory factor analysis (EFA) has long been a subject of debate in social sciences research. Finch (2020) addresses this challenge by comparing the performance of fit index difference values and parallel analysis, a well-established method in this field. The study offers …
Babcock and Hodge (2020) address a significant challenge in educational measurement: accurately equating exam scores when sample sizes are limited. Their study evaluates the performance of Rasch and classical equating methods, particularly for credentialing exams with small cohorts, and introduces data pooling as a potential solution. Background Equating ensures fairness …
Abstract This study aimed to examine the relationship between the Jouve Cerebrals Crystallized Educational Scale (JCCES) and the American College Test (ACT) by conducting a factor analysis. The dataset consisted of 60 observations, with Pearson’s correlation revealing significant associations between all variables. The factor analysis identified three factors, with the …
Roberts and Thompson (2011) conducted a thorough analysis of item parameter estimation methods within the Generalized Graded Unfolding Model (GGUM). Their work focused on the performance of the Marginal Maximum A Posteriori (MMAP) procedure compared to other approaches, including Marginal Maximum Likelihood (MML) and Markov Chain Monte Carlo (MCMC). By …
Abstract This study aimed to investigate the underlying dimensions of the Jouve Cerebrals Crystallized Educational Scale (JCCES) Mathematical Problems (MP) using Alternating Least Squares Scaling (ALSCAL). The dataset consisted of intercorrelations between 38 MP items, with 588 participants. Various dimensional solutions were assessed for the goodness of fit. A 4-dimensional …
