In standard statistical data analysis, the effects of intervention or prevention efforts are evaluated in terms of variable relations. Results from application of regression-type methods suggest whether, overall, intervention is successful. In this article, we propose using configural frequency analysis (CFA) either in tandem with regression-type…

Introduction: Differences-in-Differences (DD) is a commonly-used approach in policy evaluation for identifying the impact of an intervention or treatment. Under a parallel trend assumption (PTA), we can recover a causal effect by comparing the difference in outcomes between a treatment and a control group, both before and after an intervention was…

Curriculum-Based Measurement of Oral Reading (CBM-R) is often used to monitor student progress and guide educational decisions. Ordinary least squares regression (OLSR) is the most widely used method to estimate the slope, or rate of improvement (ROI), even though published research demonstrates OLSR's lack of validity and reliability, and…

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

Meta-analysis plays a key role in combining studies to obtain more reliable results. In social, behavioral, and health sciences, measurement units are typically not well defined. More meaningful results can be obtained by standardizing the variables and via the analysis of the correlation matrix. Structural equation modeling (SEM) with the…

Objects in the world usually have names at different hierarchical levels (e.g., "beagle," "dog," "animal"). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use…

This article describes the analysis of regression-discontinuity designs (RDDs) using the R packages rdd, rdrobust, and rddtools. We discuss similarities and differences between these packages and provide directions on how to use them effectively. We use real data from the Carolina Abecedarian Project to show how an analysis of an RDD can be…

I study the impact of novel game manipulations on user engagement using principled computational methods. Maximizing user engagement is important because it results in more profitable games in the commercial arena and better learning outcomes in the educational arena. It is then perhaps unsurprising that the study of user engagement is well…

Forensic science practitioners compare visual evidence samples (e.g. fingerprints) and decide if they originate from the same person or different people (i.e. fingerprint 'matching'). These tasks are perceptually and cognitively complex--even practising professionals can make errors--and what limited research exists suggests that existing…

Graduate Teaching Assistants (GTAs) carry a substantial instructional role in introductory courses for many mathematics and statistics departments. As a result, many GTAs have first-hand influence on the initial statistical impressions of students from a range of disciplines. But as simultaneous learners of the discipline themselves, GTAs in…

The most common and well-known meta-regression models work under the assumption that there is only one effect size estimate per study and that the estimates are independent. However, meta-analytic reviews of social science research often include multiple effect size estimates per primary study, leading to dependence in the estimates. Some…

Through the global pandemic, the single greatest challenge at universities has been the move towards digital assessment. In this classroom note, we describe our new no-exam assessment setup in a Statistics course for third-year bachelor Mechanical Engineering students. The main idea is to assess the students based on self-generated problems.…

This paper investigates the quantitative literacy and reasoning (QLR) of freshmen students pursuing a Science, Technology, Engineering, and Mathematics (STEM)-related degree but do not necessarily have a Senior High School (SHS) STEM background. QLR is described as a multi-faceted skill focused on the application of Mathematics and Statistics…

This study aimed at identifying and describing patterns of sports participation during high school among a general population of students and examining individual, social, and environmental predictors of pattern membership. A sample of 287 high school students (61% girls) from Quebec (Canada) annually reported all the organized sports in which…

Despite the centrality of data analysis to the discipline, sociology departments are currently falling short of teaching both undergraduate and graduate students crucial computing and statistical software skills. We argue that sociology instructors must intentionally and explicitly teach computing skills alongside statistical concepts to prepare…