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…

Genotype-by-environment interaction (GxE) studies probe heterogeneity in response to risk factors or interventions. Popular methods for estimation of GxE examine multiplicative interactions between individual genetic and environmental measures. However, risk factors and interventions may modulate the total variance of an epidemiological outcome…

The use of real contexts and history in the teaching of statistical principles holds much attraction in the classroom. This is especially so when the examples used are in situations that are quite out of the ordinary but can lead to further investigation by the students. Previous instances of these have been used with great effect with sporting…

We propose a novel estimator for use in a fuzzy regression discontinuity setting. The estimator can be thought of as extrapolating the traditional fuzzy regression discontinuity estimate or as an observational study that adjusts for endogenous selection into treatment using information at the discontinuity. We show that it can be motivated as…

Six-year college graduation rates for Hispanic and White students from 17 cohorts were analyzed using data from the U.S. Department of Education's IPED System. Results from regression analyses confirmed statistically significant positive linear trends for Hispanic and White students and statistically significant differences between the two…

The present study examined demographic and academic predictors of astronomy performance among a cohort of N=1909 community college students enrolled in astronomy courses in a large suburban community college during a four-year time frame, 2015-2019. The theoretical framework was based upon a deconstructive approach for predicting community college…

Linking classroom quality to separate domains of child development might neglect the transactional interactions across developmental domains. This research utilized latent profiles across academic and social-emotional development to explore which aspects of classroom quality can predict children's profiles at the classroom level. Data were drawn…

Despite the fact that third parties are present during a substantial amount of face-to-face interviews, bystander influence on respondents' response behavior is not yet fully understood. We use nine waves of the German Family Panel "pairfam" and apply fixed effects panel regression models to analyze effects of third-party presence on…

The purpose of this study is to investigate the predictive effects of maternal parenting styles and beliefs about emotions on the social skills and problem behaviours of preschoolers. The study involved 227 mothers of 3-6-year-old preschool children (M[subscript age] = 63 months). Two hierarchical regression analyses were conducted to determine to…

Open Educational Resources (OER) are regularly adopted, yet questions persist about efficacy. Do OER improve student performance? Research produces ambiguous results, because these are derived from small sample sizes, inadequate efficacy measures, and neglect of interactional effects. We examine the effect of OER on student grades using over…

We provide tools for identification and exploration of data with very large variability having power law tails. Such data describe extreme features of processes such as fire losses, flood, drought, financial gain/loss, hurricanes, population of cities, among others. Prediction and quantification of extreme events are at the forefront of the…

The administration of college financial aid is a key venue through which colleges can affect the likelihood that students will make it to graduation. We investigate the effects of an understudied yet consequential federal student aid policy: Return of Title IV Funds (R2T4). Under R2T4, students "earn" Federal Student Aid over a term or…

Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…

Machine learning (ML) methods for causal inference have gained popularity due to their flexibility to predict the outcome model and the propensity score. In this article, we provide a within-group approach for ML-based causal inference methods in order to robustly estimate average treatment effects in multilevel studies when there is cluster-level…

Although self-report surveys are widely used for data collection, data quality can vary across populations because certain groups are more likely to engage in insufficient effort responding (IER). Our study examined how different levels of the educational system--student groups, schools, and cultural contexts--affect data quality due to IER, using…