This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of confounding (marginal and conditional) that can be recovered from a simple standardization approach. We…

The use of large-scale assessments (LSAs) in education has grown in the past decade though analysis of LSAs using multilevel models (MLMs) using R has been limited. A reason for its limited use may be due to the complexity of incorporating both plausible values and weighted analyses in the multilevel analyses of LSA data. We provide additional…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

We consider the problem of bias arising from conditioning on a post-outcome collider. We illustrate this with reference to Elwert and Winship (2014) but we go beyond their study to investigate the extent to which inverse probability weighting might offer solutions. We use linear models to derive expressions for the bias arising in different kinds…

This study seeks to explore and understand the Bhutanese secondary school teacher's perception of increased Continuous Formative Assessment (CFA) weightings and the associated opportunities and challenges. Grounded on pragmatism, this study employed an explanatory sequential mixed methods design. The quantitative and qualitative data were…

We provide a novel characterization of augmented balancing weights, also known as automatic debiased machine learning (AutoDML). These popular "doubly robust" or "de-biased machine learning estimators" combine outcome modeling with balancing weights -- weights that achieve covariate balance directly in lieu of estimating and…

In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…

This study builds on the simulation framework of a recent paper by Stanley and Doucouliagos ("Research Synthesis Methods" 2023;14;515--519). S&D use simulations to make the argument that meta-analyses using partial correlation coefficients (PCCs) should employ a "suboptimal" estimator of the PCC standard error when…

Studies of test score comparability have been conducted at different stages in the history of testing to ensure that test results carry the same meaning regardless of test conditions. The expansion of at-home testing via remote proctoring sparked another round of interest. This study uses data from three licensure tests to assess potential mode…

Propensity score matching and weighting methods are often used in observational effectiveness studies to reduce imbalance between treated and untreated groups on a set of potential confounders. However, much of the prior methodological literature on matching and weighting has yet to examine performance for scenarios with a majority of treated…

Recent research has provided evidence that performance change during a student's test event can indicate the presence of test-taking disengagement. Meaningful performance change implies that some portions of the test event reflect assumed maximum performance better than others and, because disengagement tends to diminish performance,…

The logistic and confined exponential curves are frequently used in studies of growth and learning. These models, which are nonlinear in their parameters, can be estimated using structural equation modeling software. This paper proposes a single combined model, a weighted combination of both models. Mplus, Proc Calis, and lavaan code for the model…

The Monitoring the Future (MTF) study monitors historical and developmental changes in substance use prevalence among key subgroups of the general U.S. adolescent and adult population. The current study first devised and evaluated a cohort-specific pooled analysis weighing procedure for the MTF panel study that weighted back to the initial 12th…

Evaluating scale comparability in international large-scale assessments depends on measurement invariance (MI). The root mean square deviation (RMSD) is a standard method for establishing MI in several programs, such as the Programme for International Student Assessment and the Programme for the International Assessment of Adult Competencies.…

Classroom observational protocols, in which raters observe and score the quality of teachers' instructional practices, are often used to evaluate teachers for consequential purposes despite evidence that scores from such protocols are frequently driven by factors, such as rater and temporal effects, that have little to do with teacher quality. In…