There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…

This dissertation documented how undergraduate students made sense of data in news media. The participants were 30 undergraduate students enrolled in a course called "Numbers and Social Justice." The study used argument analysis (Toulmin, 2003) and ethnographic methodology to examine students' written work in a naturalistic setting.…

This paper presents a model of recurrent multinomial sequences. Though there exists a quite considerable literature on modeling autocorrelation in numerical data and sequences of categorical outcomes, there is currently no systematic method of modeling patterns of recurrence in categorical sequences. This paper develops a means of discovering…

There is extensive literature focusing on students' misconceptions in various subject domains. Several conceptual change approaches have been trying to understand how conceptual change occurs to help learners handle these misconceptions. This meta-analysis aims to integrate studies investigating the effectiveness of three types of conceptual…

Simulation studies are needed to investigate how many score categories are sufficient to treat ordered categorical data as continuous, particularly for bifactor models. The current simulation study aims to address such needs by investigating the performance of estimation methods in the bifactor models with ordered categorical data. Results support…

Within the frequentist structural equation modeling (SEM) framework, adjudicating model quality through measures of fit has been an active area of methodological research. Complicating this conversation is research revealing that a higher quality measurement portion of a SEM can result in poorer estimates of overall model fit than lower quality…

We present a method for Bayesian structural equation modeling of sample correlation matrices as correlation structures. The method transforms the sample correlation matrix to an unbounded vector using the matrix logarithm function. Bayesian inference about the unbounded vector is performed assuming a multivariate-normal likelihood, with a mean…

Purpose: Multisite mediation studies are a cornerstone in mapping out developmental processes because they probe the mechanisms of a treatment while creating key opportunities to learn from and about variation in those mechanisms across sites. Despite the prevalence of multisite studies, a significant gap in the literature is how to plan such…

Data are everywhere. Data collected from samples are often reported in the form of polls, medical studies, and advertisement information and an understanding of sampling distributions and statistical inference is important for evaluating data-based claims (Bargagliotti et al., 2020). Despite the importance of understanding statistical inference…

Statistics anxiety is a significant problem for students' learning experience in the psychological sciences. This article explores a novel teaching methodological approach during the global pandemic to improve students' performance by reducing their statistics anxiety. The subject design and teaching methodological approach were developed based on…

A common practical challenge is how to assign ability estimates to all incorrect and all correct response patterns when using item response theory (IRT) models and maximum likelihood estimation (MLE) since ability estimates for these types of responses equal -8 or +8. This article uses a simulation study and data from an operational K-12…

Regression discontinuity (RD) designs are commonly used for program evaluation with continuous treatment assignment variables. But in practice, treatment assignment is frequently based on ordinal variables. In this study, we propose an RD design with an ordinal running variable to assess the effects of extended time accommodations (ETA) for…

While correlated data methods (like random effect models and generalized estimating equations) are commonly applied in practice, students may struggle with understanding the reasons that standard regression techniques fail if applied to correlated outcomes. To this end, this article presents an in-class activity using results from Monte Carlo…

This article demonstrates how data from a biology paper, which analyzes the relationship between mass and metabolic rate for two species of marine bryozoan, can be used to teach a variety of regression topics to both introductory and advanced students. A thorough analysis requires intelligent data wrangling, variable transformations, and…

Social network data often contain missing values because of the sensitive nature of the information collected and the dependency among the network actors. As a response, network imputation methods including simple ones constructed from network structural characteristics and more complicated model-based ones have been developed. Although past…