Within each of 170 physicians, patients were randomized to access e-assist, an online program that aimed to increase colorectal cancer screening (CRCS), or control. Compliance was partial: 78.34% of the experimental patients accessed e-assist while no controls were provided the access. Of interest are the average causal effect of assignment to…

Do people think about genetic inheritance as a deterministic or probabilistic process? Do adults display systematic biases when reasoning about genetic inheritance? Knowing how adults think about genetic inheritance is valuable, both for understanding the developmental endpoint of these concepts and for identifying biases that persist even after…

Several researchers have called for schools to interpret universal screening results using posterior probabilities. Following this recommendation could require schools to move away from direct-route, single-measure screening unless base rates of risk fall within a narrow range. In this descriptive study, we investigated two questions surrounding…

Objective: In May 2021, U.S. states began implementing "vaccination lotteries" encouraging COVID-19 vaccination. Drawing from Prospect Theory and math cognition research, we tested several monetary lottery structures and their framing to determine which would best motivate unvaccinated adults. Method: In two online experiments, U.S.…

Do children think of genetic inheritance as deterministic or probabilistic? In two novel tasks, children viewed the eye colors of animal parents and judged and selected possible phenotypes of offspring. Across three studies (N = 353, 162 girls, 172 boys, 2 non-binary; 17 did not report gender) with predominantly White U.S. participants collected…

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…

Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying,…

Propensity score matching and weighting methods are often used in observational effectiveness studies to reduce imbalance between treated and untreated groups on a set of potential confounders. However, much of the prior methodological literature on matching and weighting has yet to examine performance for scenarios with a majority of treated…

Recent controversies have highlighted the importance of local school district governance, but little empirical evidence exists evaluating the quality of district policy makers or policies. In this paper, we take a novel approach to assessing school district decision making. We posit a model of rational decision making under uncertainty that…

In Bayesian statistics, the most widely used criteria of Bayesian model assessment and comparison are Deviance Information Criterion (DIC) and Watanabe-Akaike Information Criterion (WAIC). A multilevel mediation model is used as an illustrative example to compare different types of DIC and WAIC. More specifically, the study compares the…

This study examines the effectiveness of the Center for Civic Education's Project Citizen teacher professional development program and curriculum intervention in producing positive student learning outcomes that support civic engagement. Through Project Citizen, students identify and research a problem in their community, explore solutions,…

When text datasets are very large, manually coding line by line becomes impractical. As a result, researchers sometimes try to use machine learning algorithms to automatically code text data. One of the most popular algorithms is topic modeling. For a given text dataset, a topic model provides probability distributions of words for a set of…

In educational and psychological research, we are often interested in discrete latent states of individuals responding to an assessment (e.g., proficiency or non-proficiency on educational standards, the presence or absence of a psychological disorder). Diagnostic classification models (DCMs; also called cognitive diagnostic models [CDMs]) are a…

Presidential elections can be forecast using information from political and economic conditions, polls, and a statistical model of changes in public opinion over time. However, these "knowns" about how to make a good presidential election forecast come with many unknowns due to the challenges of evaluating forecast calibration and…

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…