The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be…

Measures of learning speed (i.e., the amount of learning/cumulative time learner spends engaged in an intervention) are rarely included in research designed to evaluate and compare academic interventions. We build a case that includes analyses of learning speed metrics in academic intervention research can provide more useful information for…

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…

Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…

Adaptive Comparative Judgment (ACJ), an approach to the assessment of open-ended problems which utilizes a series of comparisons to produce a standardized score, rank order, and a variety of other statistical measures, has demonstrated high levels of reliability and validity and the potential for application in a wide variety of areas. Further,…

Clinicians report primarily using functional behavioral assessment (FBA) methods that do not include functional analyses. However, studies examining the correspondence between functional analyses and other types of FBAs have produced inconsistent results. In addition, although functional analyses are considered the gold standard, their…

We present a bias-adjusted three-step estimation approach for multilevel latent class models (LC) with covariates. The proposed approach involves (1) fitting a single-level measurement model while ignoring the multilevel structure, (2) assigning units to latent classes, and (3) fitting the multilevel model with the covariates while controlling for…

Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…

This note demonstrates that measurement invariance does not guarantee meaningful and valid group comparisons in multiple-population settings. The article follows on a recent critical discussion by Robitzsch and Lüdtke, who argued that measurement invariance was not a pre-requisite for such comparisons. Within the framework of common factor…

Interviewees sometimes deliberately omit reporting some information. Such omission lies differ from other lies because all the information interviewees present may be entirely truthful. Truth tellers and lie tellers carried out a mission. Truth tellers reported the entire mission truthfully. Lie tellers were also entirely truthful but left out one…

This article is about making correction in Tarray, Singh, and Zaizai model and further improving it when stratified random sampling is necessary. This is done by using optional randomized response technique in stratified sampling using a combination of Mangat and Singh, Mangat, and Greenberg et al. models. The suggested model has been studied…

This paper argues for three aspects of tolerance with respect to QCA research: tolerance with respect to different approaches to QCA; producing QCA research with tolerance (work that is resistant to criticism); and for QCA researchers to be clear about the tolerance of the solutions they present -- especially in terms of calibration and truth…

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…

Traditional efforts around improving assessment often center on the teacher as the evaluator of work rather than the students. These assessment efforts typically focus on measuring learning rather than stimulating, promoting, or producing learning in students. This paper summarizes a study of a large sample of undergraduate students (n = 550) in…

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…