Chi-square tests based on maximum likelihood (ML) estimation of covariance structures often incorrectly over-reject the null hypothesis: [sigma] = [sigma(theta)] when the sample size is small. Reweighted least squares (RLS) avoids this problem. In some models, the vector of parameter must contain means, variances, and covariances, yet whether RLS…

Prior studies investigating the effects of non-normality in structural equation modeling typically induced non-normality in the indicator variables. This procedure neglects the factor analytic structure of the data, which is defined as the sum of latent variables and errors, so it is unclear whether previous results hold if the source of…

Structural equation modeling (SEM) applications routinely employ a trilogy of significance tests that includes the likelihood ratio test, Wald test, and score test or modification index. Researchers use these tests to assess global model fit, evaluate whether individual estimates differ from zero, and identify potential sources of local misfit,…

We examined the effect of estimation methods, maximum likelihood (ML), unweighted least squares (ULS), and diagonally weighted least squares (DWLS), on three population SEM (structural equation modeling) fit indices: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual…

Factor score regression (FSR) is a popular alternative for structural equation modeling. Naively applying FSR induces bias for the estimators of the regression coefficients. Croon proposed a method to correct for this bias. Next to estimating effects without bias, interest often lies in inference of regression coefficients or in the fit of the…

One of the aims of the current study is to specify the model providing the best fit to the data among the exploratory, the bifactor exploratory and the confirmatory structural equation models. The study compares the three models based on the model data fit statistics and item parameter estimations (factor loadings, cross-loadings, factor…

Posterior Predictive Model Checking (PPMC) is a Bayesian model checking method that compares the observed data to (plausible) future observations from the posterior predictive distribution. We propose an alternative to PPMC in the context of structural equation modeling, which we term the Poor Persons PPMC (PP-PPMC), for the situation wherein one…

Using Monte Carlo simulations, this research examined the performance of four missing data methods in SEM under different multivariate distributional conditions. The effects of four independent variables (sample size, missing proportion, distribution shape, and factor loading magnitude) were investigated on six outcome variables: convergence rate,…

Structural equation modeling (SEM) is one of the most popular multivariate statistical techniques in Turkish educational research. This study elaborates the SEM procedures employed by 75 educational research articles which were published from 2010 to 2015 in Turkey. After documenting and coding 75 academic papers, categorical frequencies and…

The purpose of this study was to assess the psychometrics properties of the Emotional Intelligence Scale and assess the measurement invariance across elite (n = 367), amateur (n = 629), and non-athletes (n = 550). In total, 1,546 participants from various sports completed the emotional intelligence scale. Several competing models were compared…

This study illustrates an integrative psychometric framework to investigate two sources of construct-relevant multidimensionality in answers to the Self-Perception Profile for Children (SPPC). Using a sample of 2,353 German students attending Grades 3 to 6, we contrasted: (a) first-order versus hierarchical and bifactor models to investigate…

Research is currently testing how the new maladaptive personality inventory for DSM (PID-5) and the well-established common Five-Factor Model (FFM) together can serve as an empirical and theoretical foundation for clinical psychology. The present study investigated the official short version of the PID-5 together with a common short version of…

As twenty-first century careers become more flexible, interest-oriented, and self-directed, the clarity of career goals alone is no longer sufficient. To better prepare students for the future world of work, engagement in proactive career behaviours is essential. The present study investigated the predictive relationships of career goal clarity,…

Spline (or piecewise) regression models have been used in the past to account for patterns in observed data that exhibit distinct phases. The changepoint or knot marking the shift from one phase to the other, in many applications, is an unknown parameter to be estimated. As an extension of this framework, this research considers modeling the…

In this commentary, David Thissen states that "Goodness-of-fit assessment for IRT models is maturing; it has come a long way from zero." Thissen then references prior works on "goodness of fit" in the index of Lord and Novick's (1968) classic text; Yen (1984); Drasgow, Levine, Tsien, Williams, and Mead (1995); Chen and…