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…

Empathy research has long emphasized accuracy when imagining other minds. We explore whether empathy can be a creative process, where people think of multiple diverging possibilities of others' experiences. We developed two tasks to measure creative empathy. First, we adapted "forward flow" to measure the dynamic unfolding of creativity…

Measurement invariance (MI) describes the equivalence of measurement models of a construct across groups or time. When comparing latent means, MI is often stated as a prerequisite of meaningful group comparisons. The most common way to investigate MI is multi-group confirmatory factor analysis (MG-CFA). Although numerous guides exist, a recent…

There is increasing interest in using factor scores in structural equation models and there have been numerous methodological papers on the topic. Nevertheless, sum scores, which are computed from adding up item responses, continue to be ubiquitous in practice. It is therefore important to compare simulation results involving factor scores to…

We investigated three different approaches for quantifying individual change and reporting it back to persons: (a) the common change score, which is obtained by first computing scale scores from two consecutive measurements and then subtract these scores from one another, (b) the ad-hoc approach, which is similar to the former approach but uses…

Mediation analysis is an important statistical tool in many research fields, where the joint significance test is widely utilized for examining mediation effects. Nevertheless, the limitation of this mediation testing method stems from its conservative Type I error, which reduces its statistical power and imposes certain constraints on its…

Random forests are a nonparametric machine learning method, which is currently gaining popularity in the behavioral sciences. Despite random forests' potential advantages over more conventional statistical methods, a remaining question is how reliably informative predictor variables can be identified by means of random forests. The present study…

Historically, organizational researchers have fully embraced frequentist statistics and null hypothesis significance testing (NHST). Bayesian statistics is an underused alternative paradigm offering numerous benefits for organizational researchers and practitioners: e.g., accumulating direct evidence for the null hypothesis (vs. 'fail to reject…

Missing data are a pervasive problem in data analysis. Three common methods for addressing the problem are (a) complete-case analysis, where only units that are complete on the variables in an analysis are included; (b) weighting, where the complete cases are weighted by the inverse of an estimate of the probability of being complete; and (c)…

A decision consistency (DC) index is an estimate of the consistency of a classification decision on an exam. More specifically, DC estimates the percentage of examinees that would have the same classification decision on an exam if they were to retake the same or a parallel form of the exam again without memory of taking the exam the first time.…

Education for Sustainable Development focuses on improving environmental knowledge to combat misinformation and promote sustainable behaviours. In two experiments, we investigated whether retrieval practice, known to foster lasting knowledge acquisition, is a useful tool for (1) increasing environmental knowledge and (2) for improving…

Research on alphabetic reading presents conflicting findings concerning the timing of orthographic and meaning processes in reading morphologically complex words. Chinese characters offer distinct visual cues for morphemes, enabling straightforward manipulations to examine orthographic and meaning processes. Guided by the Character-Word Dual…

In the field of educational robotics, it is important to understand the processes trough which child-robot interactions are established during play activities. In terms of socio-material characteristics, robots can vary widely, from more mechanical robots to more anthropomorphic ones. Research has shown that the degree of anthropomorphization of…

When it is required to estimate item parameters of a large item bank, Multiple Matrix Sampling (MMS) design provides an efficient way while minimizing the test burden on students. The current study exemplifies how to calibrate a large item pool using MMS design for various purposes, such as developing a CAT administration. The purpose of the…

We extended current knowledge by examining the performance of several Bayesian model fit and comparison indices through a simulation study using the confirmatory factor analysis. Our goal was to determine whether commonly implemented Bayesian indices can detect specification errors. Specifically, we wanted to uncover any differences in detecting…