This article is a commentary on the Focus Article, "Interpretational Confounding or Confounded Interpretations of Causal Indicators?" and a commentary that was published in issue 12(4) 2014 of "Measurement: Interdisciplinary Research & Perspectives". The authors challenge two claims: (a) Bainter and Bollen argue that the…

There are well-defined theoretical differences between the classical test theory (CTT) and item response theory (IRT) frameworks. It is understood that in the CTT framework, person and item statistics are test- and sample-dependent. This is not the perception with IRT. For this reason, the IRT framework is considered to be theoretically superior…

The assessment of differential item functioning (DIF) is routinely conducted to ensure test fairness and validity. Although many DIF assessment methods have been developed in the context of classical test theory and item response theory, they are not applicable for cognitive diagnosis models (CDMs), as the underlying latent attributes of CDMs are…

In this study, the number of factors obtained from parallel analysis, a method used for determining the number of factors in exploratory factor analysis, was compared to that of the factors obtained from eigenvalue and scree plot--two traditional methods for determining the number of factors--in terms of consistency. Parallel analysis is based on…

People with autism show superior performance to controls on the Embedded Figures Test (EFT). However, studies examining the relationship between autistic-like traits and EFT performance in neurotypical individuals have yielded inconsistent findings. To examine the inconsistency, a meta-analysis was conducted of studies that (a) compared high and…

Despite the prevalence of ordinal observed variables in applied structural equation modeling (SEM) research, limited attention has been given to model evaluation methods suitable for ordinal variables, thus providing practitioners in the field with few guidelines to follow. This study represents a first attempt to thoroughly examine the…

Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

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…

This article describes the implementation and application of a metal deposition and surface diffusion Monte Carlo simulation in a physical chemistry lab course. Here the self-diffusion of Ag atoms on a Ag(111) surface is modeled and compared to published experimental results. Both the thin-film homoepitaxial growth during adatom deposition onto a…

Traditional parallel analysis (T-PA) estimates the number of factors by sequentially comparing sample eigenvalues with eigenvalues for randomly generated data. Revised parallel analysis (R-PA) sequentially compares the "k"th eigenvalue for sample data to the "k"th eigenvalue for generated data sets, conditioned on"k"-…

Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…

A common methodological problem in the evaluation of the predictive validity of selection methods, e.g. in educational and employment selection, is that the correlation between predictor and criterion is biased. Thorndike's (1949) formulas are commonly used to correct for this biased correlation. An alternative approach is to view the selection…

Researchers often collect longitudinal data to model change over time in a phenomenon of interest. Inevitably, there will be some variation across individuals in specific time intervals between assessments. In this simulation study of growth curve modeling, we investigate how ignoring individual differences in time points when modeling change over…

This paper is about performance assessment in serious games. We conceive serious gaming as a process of player-lead decision taking. Starting from combinatorics and item-response theory we provide an analytical model that makes explicit to what extent observed player performances (decisions) are blurred by chance processes (guessing behaviors). We…

One of the central assumptions of the causal-indicator literature is that all causal indicators must be included in the research model and that the exclusion of one or more relevant causal indicators would have severe negative consequences by altering the meaning of the latent variable. In this research we show that the omission of a relevant…