Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently,…

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing…

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.…

Bayesian methods seem a natural choice for combining sources of evidence in meta-analyses. However, in practice, their sensitivity to the choice of prior distribution is much less attractive, particularly for parameters describing heterogeneity. A recent non-Bayesian approach to fixed-effects meta-analysis provides novel ways to think about…

When fitting unidimensional item response theory (IRT) models, the population distribution of the latent trait ([theta]) is often assumed to be normally distributed. However, some psychological theories would suggest a nonnormal [theta]. For example, some clinical traits (e.g., alcoholism, depression) are believed to follow a positively skewed…

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youth (Ns = 2119, 303, 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher). Empirical support for the "p"-factor diminished in multi-informant models compared with…

Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In…

The current research aimed to examine the relationships among three key aspects of the language learning process, namely, foreign language boredom (FLB), English language engagement (ELE), and academic buoyancy (AB), utilizing data collected from 2,992 Chinese language learners. In order to strengthen the accuracy and robustness of the results, we…

We study how colleges shape their students' voting habits by linking millions of SAT takers to their college-enrollment and voting histories. To begin, we show that the fraction of students from a particular college who vote varies systematically by the college's attributes (e.g. increasing with selectivity) but also that seemingly similar…

Purpose: Given the scientific and practical difficulties inherent in measuring and comparing socioeconomic deprivation (SED), and the further complexity added in cross national measurements, the main aim of this paper was to check the validity of SED measures used in PISA 2018 dataset. The SED measure used in PISA 2018 was the PISA index of…

Applying qualitative comparative analysis (QCA) to large Ns relaxes researchers' case-based knowledge. This is problematic because causality in QCA is inferred from a dialogue between empirical, theoretical, and case-based knowledge. The lack of case-based knowledge may be remedied by various robustness tests. However, being a case-based method,…

We study a California policy that loosened constraints on some local governments by lowering the share of votes required to pass school capital improvement bond referendums. We show that the policy change yielded larger tax proposals that received less support from voters, yet led to a doubling of approved spending. We show that this effect is…

Background/Context: Regression discontinuity (RD) designs are used for policy and program evaluation where subjects' eligibility into a program or policy is determined by whether an assignment variable (i.e., running variable) exceeds a pre-defined cutoff. Under a standard RD design with a continuous assignment variable, the average treatment…

Research suggests that a country does not need inequity to have high performance. However, such research has potentially suffered from confounders present in between-country comparative research (e.g., latent cultural differences). Likewise, relatively little consideration has been given to whether the situation may be different for high- or…

The precision of estimates of treatment effects in multilevel experiments depends on the sample sizes chosen at each level. It is often desirable to choose sample sizes at each level to obtain the smallest variance for a fixed total cost, that is, to obtain optimal sample allocation. This article extends previous results on optimal allocation to…