Given the rapid adoption of machine learning methods by education researchers, and the growing acknowledgment of their inherent risks, there is an urgent need for tailored methodological guidance on how to improve and evaluate the validity of inferences drawn from these methods. Drawing on an integrative literature review and extending a…

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…

In causal mediation studies that decompose an average treatment effect into indirect and direct effects, examples of post-treatment confounding are abundant. In the presence of treatment-by-mediator interactions, past research has generally considered it infeasible to adjust for a post-treatment confounder of the mediator-outcome relationship due…

Beginning with debates about the effects of smoking on lung cancer, sensitivity analyses characterizing the hypothetical unobserved conditions that can alter statistical inferences have had profound impacts on public policy. One of the most ascendant techniques for sensitivity analysis is Oster's (2019) coefficient of proportionality, which…

Meta-analysis of proportions is conceptually simple: Faced with a binary outcome in multiple studies, we seek inference on some overall proportion of successes/failures. Under common effect models, exact inference has long been available, but is not when we more realistically allow for heterogeneity of the proportions. Instead a wide range of…

Traditional cloze tests (such as the CBM-maze) may be poor measures of comprehension processes beyond the single sentence level. This paper presents an alternative, a deep cloze test with gaps that are strategically chosen to assess comprehension beyond the sentence level. To fill each gap, the reader has to draw global cohesion inferences during…

Obtaining values for latent variables in factor analysis models, also referred to as factor scores, has long been of interest to researchers. However, many treatments of factor analysis do not focus on inference about the latent variables, and even fewer do so from a Bayesian perspective. Researchers may therefore be ill-acquainted with Bayesian…

This study explored children's causal reasoning about the past and future. U.S. adults (n = 60) and 3-to-6-year-olds (n = 228) from an urban, middle-class population (49% female; [approximately] 45% white) participated between 2017 and 2019. Participants were told three-step causal stories and asked about the effects of a change to the second…

In pursuing goals, people seek favorable odds. We investigated whether young children use this fact to infer goals from people's actions across two experiments on Canadian 3- to 7-year-old children (N = 316; 167 girls, 149 boys). Participants' demographic information was not formally collected, but the region is predominantly middle-class and…

Children can acquire novel word meanings by using pragmatic cues. However, previous literature has frequently focused on in-the-moment word-to-meaning mappings, not delayed retention of novel vocabulary. Here, we examine how children use pragmatics as they learn and retain novel words. Thirty-three younger children (mean age: 5.0, range: 4.0-6.0,…

This paper informs users of data collected in international large-scale assessments (ILSA), by presenting argumentsunderlining the importance of considering two design features employed in these studies. We examine a commonmisconception stating that the uncertainty arising from the assessment design is negligible compared with that arisingfrom the…

Predicates like "coloring-the-star" denote events that have a temporal duration and a culmination point ("telos"). When combined with perfective aspect (e.g., "Valeria has colored the star"), a culmination inference arises implying that the action has stopped, and the star is fully colored. While the perfective aspect…

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…

This report characterizes forms of dialogic support that a sixth-grade teacher generated during whole-class and small-group conversations to help students develop a practice of statistical modeling. During four weeks of instruction, students constructed and revised models to account for variability and uncertainty across a variety of random…

A necessary step in applying bi-factor models is to evaluate the need for domain factors with a general factor in place. The conventional null hypothesis testing (NHT) was commonly used for such a purpose. However, the conventional NHT meets challenges when the domain loadings are weak or the sample size is insufficient. This article proposes…