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 study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…

A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…

A Monte Carlo simulation study was conducted to examine the performance of [alpha], [lambda]2, [lambda][subscript 4], [lambda][subscript 2], [omega][subscript T], GLB[subscript MRFA], and GLB[subscript Algebraic] coefficients. Population reliability, distribution shape, sample size, test length, and number of response categories were varied…

Multifinality, equifinality, and fanning are important developmental concepts that emphasize understanding interindividual variability in trajectories over time. However, each concept implies that there are points in a developmental window where interindividual variability is more limited. We illustrate the multifinality concept under…

A nonconverged Markov chain can potentially lead to invalid inferences about model parameters. The purpose of this study was to assess the effect of a nonconverged Markov chain on the estimation of parameters for mixture item response theory models using a Markov chain Monte Carlo algorithm. A simulation study was conducted to investigate the…

In exploratory factor analysis, although the researchers decide which items belong to which factors by considering statistical results, the decisions taken sometimes can be subjective in case of having items with similar factor loadings and complex factor structures. The aim of this study was to examine the validity of classifying items into…

The recent popularity of models that capture the dynamic coevolution of both network structure and behavior has driven the need for summary indices to assess the adequacy of these models to reproduce dynamic properties of scientific or practical importance. Whereas there are several existing indices for assessing the ability of the model to…

This article offers an approach to examining differential item functioning (DIF) under its item response theory (IRT) treatment in the framework of confirmatory factor analysis (CFA). The approach is based on integrating IRT- and CFA-based testing of DIF and using bias-corrected bootstrap confidence intervals with a syntax code in Mplus.

Researchers continue to be interested in efficient, accurate methods of estimating coefficients of covariates in mixture modeling. Including covariates related to the latent class analysis not only may improve the ability of the mixture model to clearly differentiate between subjects but also makes interpretation of latent group membership more…

This paper aims to extend understanding of the business and societal impact of academic research. From a business school perspective, it has taken stock of the role of academic research and relevance in business and society. The proposed conceptual framework highlights the forces influencing the pursuit of academic rigour and relevance in…

This study compares the performance of two estimation algorithms of new usage, the Metropolis-Hastings Robins-Monro (MHRM) and the Hamiltonian MCMC (HMC), with two consolidated algorithms in the psychometric literature, the marginal likelihood via EM algorithm (MML-EM) and the Markov chain Monte Carlo (MCMC), in the estimation of multidimensional…

The usability of computer interfaces has a major influence on learning. Optimising the usability of e-learning resources is therefore essential. However, this may be neglected because of time and monetary constraints. User testing is a common approach to usability evaluation and involves studying typical end-users interacting with the application…

Combining multiple regression estimates with meta-analysis has continued to be a difficult task. A variety of methods have been proposed and used to combine multiple regression slope estimates with meta-analysis, however, most of these methods have serious methodological and practical limitations. The purpose of this study was to explore the use…

Testing factorial invariance has recently gained more attention in different social science disciplines. Nevertheless, when examining factorial invariance, it is generally assumed that the observations are independent of each other, which might not be always true. In this study, we examined the impact of testing factorial invariance in multilevel…