In the social sciences, measurement scales often consist of ordinal items and are commonly
analyzed using factor analysis. Either data are treated as continuous, or a discretization …

Abstract In Structural Equation Modeling (SEM), the measurement part and the structural
part are typically estimated simultaneously via an iterative Maximum Likelihood (ML) …

Data pooling is a powerful strategy in empirical research. However, combining multiple
datasets often results in a large amount of missing data, as variables that are not present in …

This article delves into the often-overlooked metric of percentage of variance accounted for
in structural equation models (SEM). The goodness of fit index (GFI) provides the …

In confirmatory factor analysis (CFA), model parameters are usually estimated by iteratively
minimizing the Maximum Likelihood (ML) fit function. In optimal circumstances, the ML …

In the Anthropocene, there is a strong interlinkage among water, energy, and the
environment. The water-energy-environment nexus (WEEN) has been vigorously advocated …

Abstract Recently, Asparouhov and Muthén Structural Equation Modeling: A
Multidisciplinary Journal, 28, 1–14,(,) proposed a variant of the Wald test that uses Markov …

Monte Carlo simulation studies are among the primary scientific outputs contributed by
methodologists, guiding application of various statistical tools in practice. Although …

We present PLSIM, a new method for generating nonnormal data with a pre-specified
covariance matrix that is based on coordinate-wise piecewise linear transformations of …

In the social sciences, accurately identifying the dimensionality of measurement scales is
crucial for understanding latent constructs such as anxiety, happiness, and self-efficacy. This …