Fit indices are descriptive measures that can help evaluate how well a confirmatory factor analysis (CFA) model fits a researcher's data. In multigroup models, before between-group comparisons are made, fit indices may be used to evaluate measurement invariance by assessing the degree to which multiple groups' data are consistent with increasingly…

Children's fuzziness leads to increased variance in the data, data loss, and high dropout rates in developmental studies. This study investigated the importance of 20 factors on the person (child, caregiver, experimenter) and situation (task, method, time, and date) level for the data quality as indicated via the number of valid trials in 11…

Researchers continue to choose PCA in scale development and adaptation studies because it is the default setting and overestimates measurement quality. When PCA is utilized in investigations, the explained variance and factor loadings can be exaggerated. PCA, in contrast to the models given in the literature, should be investigated in…

In this article, we pursue two points of discussion. First, a new illustration is presented of the person-oriented tenet according to which it can be hazardous to generalize to the individual results that are based on the analysis of aggregated data. Second, it is illustrated that taking into account serial dependence information can result in not…

Inductive/deductive hybrid thematic analysis offers significant opportunities for researchers, but its application within integrative mixed methods research has yet to be fully explored. Firstly, this article contributes by demonstrating the compatibility of inductive/deductive hybrid thematic analysis with quantitative work in a mixed methods…

Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method.…

Transfer beliefs are understudied in the training transfer field, whereas structural equation modelling (SEM) has been a widely used technique to study transfer models. New methodologies are needed to study training transfer and network analysis (NA) has emerged as a new approach that provides a visual representation of a given network. We…

Exploratory graph analysis (EGA) is a commonly applied technique intended to help social scientists discover latent variables. Yet, the results can be influenced by the methodological decisions the researcher makes along the way. In this article, we focus on the choice regarding the number of factors to retain: We compare the performance of the…

This paper evaluates the use of Factor Analysis (FA) in English education research in Korea and suggests improvements in methodology. A detailed coding protocol was used to review 179 FA cases from 12 major English education journals (2014-2023). The review identified several key issues, including small sample sizes and lenient criteria for sample…

We describe a data mining pipeline to convert data from educational systems into knowledge component (KC) models. In contrast to other approaches, our approach employs and compares multiple model search methodologies (e.g., sparse factor analysis, covariance clustering) within a single pipeline. In this preliminary work, we describe our approach's…

Statistical learning is a key concept in our understanding of language acquisition. Ample work has highlighted its role in numerous linguistic functions--yet statistical learning is not a unitary construct, and its consistency across different language properties remains unclear. In a meta-analysis of auditory-linguistic statistical learning…

Exploratory factor analysis is a statistical method commonly used in psychological research to investigate latent variables and to develop questionnaires. Although such self-report questionnaires are prone to missing values, there is not much literature on this topic with regard to exploratory factor analysis--and especially the process of factor…

This paper analyzes the research performance evolution of a scientific institute, from its genesis through various stages of development. The main aim is to obtain, and visually represent, bibliometric evidence of the correlation of organizational changes on the development of its scientific performance; particularly, structural and leadership…

The use of structural equation modeling (SEM) techniques in social work has increased over the last two decades. We therefore conducted a systematic review to understand the extent to which SEM is utilized in social work research, given that statistical training is now becoming a part of social work doctoral education. For our review, we utilized…

The alternative human capital evaluation method proposed is implemented via two methods: principal component analysis and discriminant analysis. The first method classifies the research laboratory activities in homogeneous clusters, while the second method standardizes their scores. The proposed method is sitting in the activity-based management…