The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…

Students that classify as having growth mindsets rather than fixed mindsets enjoy greater academic success. This finding has been repeated in a variety of contexts and encourages teachers and researchers to develop growth mindsets in students. However, neutral and negative conclusions from some mindset intervention studies raise questions about…

Growth mixture modeling (GMM) is a methodological tool used to represent heterogeneity in longitudinal datasets through the identification of unobserved subgroups following qualitatively and quantitatively distinct trajectories in a population. These growth trajectories or functional forms are informed by the underlying developmental theory, are…

Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…

Assessing student achievement over multiple years is complicated by students' annual matriculation through different classrooms. The process of matriculation, or annual classroom change, threatens the validity of statistical inferences because it violates the independence of observations necessary in a regression context. The current study…

The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…

This article examines the role of the Great Depression in shaping the intergenerational mobility of some of the most upwardly mobile cohorts of the twentieth century. Using newly linked census and vital records from the Longitudinal, Intergenerational Family Electronic Micro-database, we examine the occupational and educational mobility of more…

There is an ongoing debate in higher education about the value of broad programmes versus specialised programmes. Educational professionals argue that students use the space provided by broad programmes to develop interests in diverse domains, while the scope of specialised programmes allows students to converge in interests. The present study…

Considerable interest lies in the growth in educational achievement that occurs over the course of a child's schooling. This paper demonstrates a simple but effective approach for the comparison of growth rates, drawing on a method first proposed some 80 years ago and applying it to data from the Australian National Assessment Program. The…

This paper examines the developmental trajectories of students' self-authored worldview commitments over four years of college and the reasons they offered for making associated developmental gains. Through a longitudinal, mixed methods approach, we unearthed four distinctive developmental trajectories of a nationally-representative cohort of…

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…

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…

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,…

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…