Detection of metal ions in solution has been performed without employing H[subscript 2]S or any other sulfide materials. The new method is free from the interference from anions. Identification of Na[superscript +], K[superscript +], and NH[subscript 4][superscript +] has been made possible directly from an aqueous extract of the sample mixture. A…

Meta-analyses of educational research findings frequently involve statistically dependent effect size estimates. Meta-analysts have often addressed dependence issues using ad hoc approaches that involve modifying the data to conform to the assumptions of models for independent effect size estimates, such as by aggregating estimates to obtain one…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

Double-scoring constructed-response items is a common but costly practice in mixed-format assessments. This study explored the impacts of Targeted Double-Scoring (TDS) and random double-scoring procedures on the quality of psychometric outcomes, including student achievement estimates, person fit, and student classifications under various…

Numerous methods exist to determine the optimal number of classes when using latent profile analysis (LPA), but none are consistently correct. Recently, the likelihood incremental percentage per parameter (LI3P) was proposed as a model effect-size measure. To evaluate the LI3P more thoroughly, we simulated 50,000 datasets, manipulating factors…

In recent years, educators, administrators, policymakers, and measurement experts have called for assessments that support educators in making better instructional decisions. One promising approach to measurement to support instructional decision-making is diagnostic classification models (DCMs). DCMs are flexible psychometric models that…

False alarming, or detecting an error when there is not one, is a pervasive problem across numerous industries. The present study investigated the role of elaboration, or additional information about non-error differences in complex visual displays, for mitigating false error responding. In Experiment 1, learners studied errors and non-error…

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…

A common problem in the analysis of multiple data sources, including individual participant data meta-analysis (IPD-MA), is the misclassification of binary variables. Misclassification may lead to biased estimators of model parameters, even when the misclassification is entirely random. We aimed to develop statistical methods that facilitate…

This study proposes a Bayesian method for diagnostic classification models (DCMs) for a partially known Q-matrix setting between exploratory and confirmatory DCMs. This Q-matrix setting is practical and useful because test experts have pre-knowledge of the Q-matrix but cannot readily specify it completely. The proposed method employs priors for…

In many large-scale testing programs, examinees are frequently categorized into different performance levels. These classifications are then used to make high-stakes decisions about examinees in contexts such as in licensure, certification, and educational assessments. Numerous approaches to estimating the consistency and accuracy of this…

There is a need to continue to amplify the value of occupational therapy for individuals with disabilities who are transitioning from secondary education to adult settings, such as vocational and post-secondary educational environments. Literature evidences a lack of practitioner knowledge of assessments and evaluations within the scope of…

The causal view of categories assumes that categories are represented by features and their causal relations. To study the effect of causal knowledge on categorization, researchers have used Bayesian causal models. Within that framework, categorization may be viewed as dependent on a likelihood computation (i.e., the likelihood of an exemplar with…

In this article we attempt to reconstruct the tacit and implicit notions of quality in the humanities. This reconstruction is based on a series of semi-structured qualitative interviews with 33 humanities scholars. Applying Max Weber's theory of authority, we argue the quality notions have two different sources--external and internal. External…

Evaluation competency frameworks across the globe regard evaluation approaches as important to know and use in practice. Prior classifications have been developed to aid in understanding important differences among varying approaches. Nevertheless, there is an opportunity for a new classification of evaluation approaches, in particular one that is…