Missing data in scientific research go hand in hand with assumptions about the nature of the missingness. When dealing with missing values, a set of beliefs has to be formulated about the extent to which the observed data may also hold for the missing parts of the data. It is vital that the validity of these missingness assumptions is verified,…

Researchers frequently use Rasch models to analyze survey responses because these models provide accurate parameter estimates for items and examinees when there are missing data. However, researchers have not fully considered how missing data affect the accuracy of dimensionality assessment in Rasch analyses such as principal components analysis…

One of the most vexing challenges facing developmental researchers today is the statistical modeling of two or more behaviors as they unfold jointly over time. Although quantitative methodologists have studied these issues for more than half a century, no widely agreed-upon principled strategy exists to empirically analyze codevelopmental…

Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…

This study compares latent profiles derived from student subgroups of varying levels of mathematical skills defined by achievement and ability assessment scores. Achievement and ability cut scores for identifying students at both ends of the mathematics spectrum were applied and the resulting latent profiles within each condition were compared.…

The global push to reorient social sciences in an increasingly technical direction might have a clear labour-market justification, but the efforts face headwinds from both faculty and students. This research is concerned with the fear that students would resist such a reorientation. Much of the pedagogic social-science research seeks ways to…

The education system has relied on conventional single-score assessments, which provide limited insights into students' cognitive abilities. Cognitive diagnostic assessment (CDA) offers a promising alternative by providing detailed information on students' cognitive processes. The review aims to explore the recent trends of cognitive diagnostic…

Clustering methods are often used in physics education research (PER) to identify subgroups of individuals within a population who share similar response patterns or characteristics. Among these, k-means (or k-modes, for categorical data) is one of the most commonly used clustering methods in PER. This algorithm, however, is distance-based rather…

Background/Context: The application of statistical modeling techniques to high-dimensional educational data presents methodological challenges, particularly the study of student transfer between higher education institutions. Over 13% of new college students each year are transfer students (National Student Clearinghouse Research Center, 2025) and…

Statistical knowledge is required for students in a range of disciplines. However, there are limited educator resources that exist for applying statistics to solve real-world problems. This investigation provides one approach to teaching statistics using entrepreneurial-minded learning (as a way to connect real-world applications and value…

For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…

Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…

Although the critical research cannon is often associated with qualitative scholars, there is a growing number of critical scholars who are refusing positivist-informed quantitative analyses. However, as a growing number of education scholars engaged in critical approaches to quantitative inquiry, instances of conflation began to surface. We…

The paradigm on which a methodological approach is developed determines the situations in which its application will be most appropriate. The quantitative approach implies a positivist paradigm, the basis of which is cause-and-effect relationships, as well as the questioning and verifying of existing theories. Positivism aims to prove that…

Meta-analytic models for dependent effect sizes have grown increasingly sophisticated over the last few decades, which has created challenges for a priori power calculations. We introduce power approximations for tests of average effect sizes based upon several common approaches for handling dependent effect sizes. In a Monte Carlo simulation, we…