Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…

Outcomes from a large cluster-randomized study of "Second Step"©, a commonly adopted universal SEL program, have previously demonstrated small, teacher-reported effects on social-emotional competencies for subgroups of students. Given the size of investment in large RCT studies, and in SEL programming, replication attempts are warranted,…

Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…

Growth mixture models (GMMs) are a popular method to uncover heterogeneity in growth trajectories. Harnessing the power of GMMs in applications is difficult given the prevalence of nonconvergence when fitting GMMs to empirical data. GMMs are rooted in the random effect tradition and nonconvergence often leads researchers to modify their intended…

This dissertation consists of three chapters that contribute to the fields of macroeconomics, economic development, and entrepreneurship. In the first chapter, "Entrepreneurship Selection and Performance in the U.S. and Across Countries: The Role of Human Capital," I seek to establish a set of stylized facts related to entrepreneurship…

A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b) full information maximum likelihood using the expectation-maximization algorithm, (c) multiple imputation, (d) a two-stage multiple…

Studies on utility value, metacognitive strategies, and achievement have usually examined these variables in a static manner. However, each of these variables changes across time and the relationships among them are dynamic. Hence, studies that examine changes in individual trajectories (change in each variable over time) and concurrent…

As research must measure and precisely assess the effects of changes and advances in an area of endeavor, mathematics has played. It continues to play a key role in developing realms of science and technology. Academic performance is an important factor in determining an individual's success or failure in mathematics. Mathematics is obligatory in…

JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…

In this study, longitudinal relations between achieving language and mathematics with perceived creativity and predicting academic achievement in high school among academically higher achieving students (N = 214) are examined. Data from the Korean Educational Longitudinal Study 2013 (Waves 1 [approximately] 7, 2013 [approximately] 2019; KEDI,…

The number of low-performing schools has drastically increased since COVID-19. During the 2018-2019 school year, there were 488 low-performing schools (North Carolina Department of Public Instruction, 2024). The number increased to 736 schools during the 2023- 2024 school year, a 50.8% increase (North Carolina Department of Public Instruction,…

Modeling within-person change over time and between-person differences in change over time is a primary goal in prevention science. When modeling change in an observed score over time with multilevel or structural equation modeling approaches, each observed score counts toward the estimation of model parameters equally. However, observed scores…

Rambo-Hernandez and McCoach's analysis into the longitudinal growth of high-achieving students offered two conclusions about the reading growth of high achieving students: high-achieving students lose less ground in reading during the summer, but they exhibit less growth over the school year. This study will seek to replicate the reading results…

During the past decade, cognitive diagnostic models (CDMs) have become prevalent in providing diagnostic information for learning. Cognitive diagnostic models have generally focused on single cross-sectional time points. However, longitudinal assessments have been commonly used in education to assess students' learning progress as well as…

Teachers and school leaders frequently express a disconnect in the purpose and importance of teacher evaluation, particularly as it relates to educator growth. At the same time, some schools are beginning to communicate student growth through a standards-based grading philosophy. One way schools might "walk the talk" of their grading…