Nonlinear mixed-effects models are models in which one or more coefficients of the growth model enter in a nonlinear manner, such as appearing in the exponent of the growth function. In their applications, the within-individual residuals are often assumed to be independent with constant variance across time, an assumption that implies that the…

Symbols are a cornerstone of the written language of mathematics and mathematical sciences. However, variations in their use pose a constant challenge to students. This paper reports data from first year undergraduate students studying mathematics, statistics and/or physics collected using surveys and interviews. It became clear that multiple uses…

The data sets used in statistics education have changed over time, from mathematically "well-behaved" ones that facilitated computation, to more context-rich sources and now, with the increasing influence of data science practices, to "found" data, often from open data sites. As data sources change, it is important for…

This article features a collaborative autoethnography of its two authors: we are instructors, also life partners, whose teaching of statistics has been transformed through significant, intimate conversations. We implemented the collaborative autoethnography within an integrated theoretical framework, designed to underpin the function of…

The article focuses on estimating effects in nonrandomized studies with two outcome measurement occasions and one predictor variable. Given such a design, the analysis approach can be to include the measurement at the previous time point as a predictor in the regression model (ANCOVA), or to predict the change-score of the outcome variable…

This study examines the role of language environment (number of conversational turns) in the development of socioemotional competencies between 18 and 30 months. The language environment of 43 infants and their social-emotional competencies were measured at 18 months and again at 30 months. Multiple regressions showed a significant contribution of…

An appreciation of experimental design is an important aspect of introductory statistics teaching in a wide range of applied disciplines, including medical statistics. Understanding the impact of design decisions on the choice of analysis method and subsequent interpretation of results can help to embed the importance of statistical thinking in…

Objective: To examine the association between fraternity/sorority membership and athlete status with tobacco use by tobacco product type. Participants: Undergraduate college students who participated in the Spring 2017 National College Health Assessment-II Survey (n = 47,821). Methods: Prevalence of current (past-30 day) cigarette smoking,…

Single case experimental design (SCED) is an indispensable methodology when evaluating intervention efficacy. Despite long-standing success with using visual analyses to evaluate SCED data, this method has limited utility for conducting meta-analyses. This is critical because meta-analyses should drive practice and policy in behavioral disorders…

Past studies have documented some pre-service teachers' (PSTs) difficulties in reasoning about sampling variability. This study adds to the body of literature by investigating the ideas that PSTs employ in reasoning about sampling variability, and by conjecturing what is behind the difficulties especially during the contextuality episodes. This…

Estimates of various variance components, universe score variance, measurement error variances, and generalizability coefficients, like all statistics, are subject to sampling variability, particularly in small samples. Such variability is quantified traditionally through estimated standard errors and/or confidence intervals. The paper derived new…

Often clinicians are interested in determining whether a subject's measurement falls within a normal range, defined as a range of values of a continuous outcome which contains some proportion (eg, 95%) of measurements from a healthy population. Several studies in the biomedical field have estimated reference ranges based on a meta-analysis of…

The latest edition highlights information about schools, enrollment and staffing patterns for Catholic elementary and secondary schools for the 2020-2021 school year. [For the 2019-2020 edition, see ED613136.]

It is not always clear how to adjust for control data in causal inference, balancing the goals of reducing bias and variance. We show how, in a setting with repeated experiments, Bayesian hierarchical modeling yields an adaptive procedure that uses the data to determine how much adjustment to perform. The result is a novel analysis with increased…

This dissertation is a collection of three papers. The first is a conceptual paper, followed by two data analysis papers. All three papers examine the connection between structural equation models and regression models, and how one may better learn, research and apply structural equation models when structural equation models are thought of as…