Consistency and coverage are two core parameters of model fit used by configurational comparative methods (CCMs) of causal inference. Among causal models that perform equally well in other respects (e.g., robustness or compliance with background theories), those with higher consistency and coverage are typically considered preferable. Finding the…

Accounting for model misspecification in Bayesian structural equation models is an active area of research. We present a uniquely Bayesian approach to misspecification that models the degree of misspecification as a parameter--a parameter akin to the correlation root mean squared residual. The misspecification parameter can be interpreted on its…

Item response theory (IRT) models the relationship between the possible scores on a test item against a test taker's attainment of the latent trait that the item is intended to measure. In this study, we compare two models for tests with polytomously scored items: the optimal scoring (OS) model, a nonparametric IRT model based on the principles of…

In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…

In the literature of modern psychometric modeling, mostly related to item response theory (IRT), the fit of model is evaluated through known indices, such as X[superscript 2], M2, and root mean square error of approximation (RMSEA) for absolute assessments as well as Akaike information criterion (AIC), consistent AIC (CAIC), and Bayesian…

The purpose of this study was to evaluate the degree of classification quality in the basic latent class model when covariates are either included or are not included in the model. To accomplish this task, Monte Carlo simulations were conducted in which the results of models with and without a covariate were compared. Based on these simulations,…

Diagnostic classification models (DCMs) are psychometric models that can be used to estimate the presence or absence of psychological traits, or proficiency on fine-grained skills. Critical to the use of any psychometric model in practice, including DCMs, is an evaluation of model fit. Traditionally, DCMs have been estimated with maximum…

Person-fit analyses are commonly used to detect aberrant responding in self-report data. Nonparametric person fit statistics do not require fitting a parametric test theory model and have performed well compared to other person-fit statistics. However, detection of aberrant responding has primarily focused on dominance response data, thus the…

Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit…

Factor mixture modeling (FMM) has been increasingly used to investigate unobserved population heterogeneity. This study examined the issue of covariate effects with FMM in the context of measurement invariance testing. Specifically, the impact of excluding and misspecifying covariate effects on measurement invariance testing and class enumeration…

Many large-scale performance assessments include score resolution procedures for resolving discrepancies in rater judgments. The goal of score resolution is conceptually similar to person fit analyses: To identify students for whom observed scores may not accurately reflect their achievement. Previously, researchers have observed that…

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…

It is common practice for assessment programs to organize qualifying sessions during which the raters (often known as "markers" or "judges") demonstrate their consistency before operational rating commences. Because of the high-stakes nature of many rating activities, the research community tends to continuously explore new…

As the theme of the 2022 annual meeting of the American Education Research Association, cultivating equitable education systems has gained renewed attention amid an increasingly diverse society. However, systemic inequalities persist for traditionally underserved student populations. As a way to better address diverse students' needs, it is of…

Several multivariate models are motivated to answer similar developmental questions regarding within-person (intraindividual) effects between 2 or more constructs over time, yet the within-person effects tested by each model are distinct. In this article, the authors clarify the types of within-person inferences that can be made from each model.…