The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…

We present a set of studies the objective of which was to test the robustness of the acknowledgment of earned entitlement effect across different experimental modes and populations. We present three sets of results. The first is derived from a between-subject analysis of two independent, but comparable samples of nonstudent adults. One sample…

In this study, the performance of the Lambda Coefficient of Rater-Mediated Agreement was evaluated with other chance-corrected agreement coefficients. Lambda is grounded in rater-mediated assessment theory and was developed as an alternative to Kappa (Cohen, 1960) and other chance-corrected agreement coefficients. Lambda has two variations, a…

We study the returns to experience in teaching, estimated using supervisor ratings from classroom observations. We describe the assumptions required to interpret changes in observation ratings over time as the causal effect of experience on performance. We compare two difference-in-differences strategies: the two-way fixed effects estimator common…

We extended current knowledge by examining the performance of several Bayesian model fit and comparison indices through a simulation study using the confirmatory factor analysis. Our goal was to determine whether commonly implemented Bayesian indices can detect specification errors. Specifically, we wanted to uncover any differences in detecting…

Marginal maximum likelihood, a common estimation method for item response theory models, is not inherently a Bayesian procedure. However, due to estimation difficulties, Bayesian priors are often applied to the likelihood when estimating 3PL models, especially with small samples. Little focus has been placed on choosing the priors for marginal…

The goal of this paper is to find better ways to estimate the internal consistency reliability of scores on tests with a specific type of design that are often encountered in practice: tests with constructed-response items clustered into sections that are not parallel or tau-equivalent, and one of the sections has only one item. To estimate the…

Matching-adjusted indirect comparison (MAIC) enables indirect comparisons of interventions across separate studies when individual patient-level data (IPD) are available for only one study. Due to its similarity with propensity score weighting, it has been speculated that MAIC can be combined with outcome regression models in the spirit of…

Binary outcomes are often analyzed in cluster randomized trials (CRTs) using logistic regression and cluster robust standard errors (CRSEs) are routinely used to account for the dependent nature of nested data in such models. However, CRSEs can be problematic when the number of clusters is low (e.g., < 50) and, with CRTs, a low number of…

When comparing relations and means of latent variables, it is important to establish measurement invariance (MI). Most methods to assess MI are based on confirmatory factor analysis (CFA). Recently, new methods have been developed based on exploratory factor analysis (EFA); most notably, as extensions of multi-group EFA, researchers introduced…

The use of discrete categorical formats to assess psychological traits has a long-standing tradition that is deeply embedded in item response theory models. The increasing prevalence and endorsement of computer- or web-based testing has led to greater focus on continuous response formats, which offer numerous advantages in both respondent…

While significant attention has been given to test equating to ensure score comparability, limited research has explored equating methods for rater-mediated assessments, where human raters inherently introduce error. If not properly addressed, these errors can undermine score interchangeability and test validity. This study proposes an equating…

The artificial intelligence methods might be applied to see through the education problems, and make effective prediction and decision. The transformation from data to decision are inseparable from the learning analytics. In order to solve the dynamic multi-objective decision problems, a decision learning algorithm is designed to analyze the…

A full structural equation model (SEM) typically consists of both a measurement model (describing relationships between latent variables and observed scale items) and a structural model (describing relationships among latent variables). However, often researchers are primarily interested in testing hypotheses related to the structural model while…

In the United States high school students may take college level courses that count for credit in both high school and college, often called dual enrollment. Students may take courses at their high school from certified instructors or at a local college. We investigate possible differences between these two groups of students using student level…