Item Response Theory (IRT) is commonly used in educational assessments to model the relationship between one or more latent traits and the observed responses. Traditional IRT methods often rely on frequentist approaches, which can be limited by assumptions and computational constraints. This article aims to introduce school psychology researchers…

Applied educational researchers may be interested in exploring random slope effects in multilevel models, such as when examining individual growth trajectories with longitudinal data. Random slopes are effects for which the slope of an individual-level coefficient varies depending on group membership, however these effects can be difficult to…

Background/Context: Methodological background: Meta-analysis typically depends on the assumption that true effects follow the normal distribution. While assuming normality of effect "estimates" is often supported by a central limit theorem, normality for the distribution of interventions' "true" effects is a computational…

Jokes, cartoons, songs, poems, and games can be useful ways to engage students in discussion and learning key concepts about regression.

Many college students consider statistical courses as frightening and demanding, yielding high anxiety and low competence, and correlating with maladaptive academic behaviors and low achievement. With undergraduate students, the present pre-post study compared a supportive online teaching program utilizing mandatory statistical exercises (n = 37)…

The purpose of this study was to inform the dissemination of a project-based statistics curriculum by identifying institutional and instructor characteristics that predict its implementation. Data were drawn from pre- and post-workshop surveys completed by 67 instructors attending a one-and-a-half-day professional development workshop on…

The objective of this article is to discuss the development of statistical and probabilistic reasoning in childhood as a result of an interdisciplinary project, involving the fields of mathematics, statistics, and life sciences. This is a case study with three 10-year-old students from a Brazilian school. The children's oral and written narratives…

In recent years, numeracy has had an increasing focus in the Australian educational system, with policies and assessments in place for both students and teachers. In order to address the requirements of their careers, teachers need to have sufficient numeracy capabilities. In our study, we explored the numeracy capabilities of post-graduate…

Extensive research has established that successful learning from an example is conditional on an important learning activity: self-explanation. Moreover, a model for learning from examples suggests that self-explanation quality mediates effects of examples on learning outcomes (Atkinson et al. in Rev Educ Res 70:181-214, 2000). We investigated…

When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior uncertainty. And, even if the most important modes can be found, it is difficult to evaluate their relative weights in…

The Pearson correlation coefficient can be recovered from the two least squares regression lines y[with circumflex] = b[subscript 0] + b[subscript 1]x and x[with circumflex] = a[subscript 0] + a[subscript 1]y without any data. This can be done both algebraically and geometrically. This can be done without data even when the scales of the variables…

We study flexible Bayesian methods that are amenable to a wide range of learning problems involving complex high dimensional data structures, with minimal tuning. We consider parametric and semiparametric Bayesian models, that are applicable to both static and dynamic data, arising from a multitude of areas such as economics, finance and…

Researchers are encouraged to report effect size statistics to quantify treatment effects or effects due to group differences. However, estimates of effect sizes, most commonly Cohen's "d," make assumptions about the distribution of data that are not always true. An alternative nonparametric estimate of effect size, relying on the median…

The topic of Bayesian updating is explored using standard and non-standard dice as an intuitive and motivating model. Details of calculating posterior probabilities for a discrete distribution are provided, offering a different view to P-values. This article also includes the stars and bars counting technique, a powerful method of counting that is…

Causal analyses typically focus on average treatment effects. Yet for substantive research on topics like inequality, interest extends to treatments' distributional consequences. When individuals differ in their responses to treatment, three types of inequality may result. Treatment may shape inequalities between subgroups defined by pretreatment…