Textbook data is essential for teaching statistics and data science methods because it is clean, allowing the instructor to focus on methodology. Ideally textbook datasets are refreshed regularly, especially when they are subsets taken from an ongoing data collection. It is also important to use contemporary data for teaching, to imbue the sense…

Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…

In this article, we explore the use of Facebook targeted advertisements for the collection of survey data. We illustrate the potential of survey sampling and recruitment on Facebook through the example of building a large employee--employer linked data set as part of The Shift Project. We describe the workflow process of targeting, creating, and…

Longitudinal research is often interested in identifying correlates of heterogeneity in change. This paper compares three approaches for doing so: the mixed-effects model (latent growth curve model), the growth mixture model, and structural equation model trees. Each method is described, with special focus given to how each structures…

Most quantitative analyses in workforce education are affected by missing data. Traditional approaches to remedy missing data problems often result in reduced statistical power and biased parameter estimates due to systematic differences between missing and observed values. This article examines the treatment of missing data in pertinent…

As this issue of the "Future of Children" makes clear, there is much yet to learn about military children and their families. A big part of the reason, write Anita Chandra and Andrew London, is the lack of sufficiently robust sources of data. Until more and better data are collected about military families, Chandra and London say, it…

Sparked by the current economic situation in the U.S., policymakers have begun to shift their concern from solely concentrating on the preparation of students for college to preparing them for the workforce as well. Thus, it is time for CTE to understand its impact on students' long-term trajectories. The purpose of this study was to predict…

There has been a general decline in the dropout rate and an increase in the high school completion rate over the last three decades. This research investigates causes for the decline in the dropout rate over the periods using decomposition analysis. Traditional cross-section analysis was inadequate to perform this task. Using the two cohort…

"Growth mixture models" (GMMs) with nonignorable missing data have drawn increasing attention in research communities but have not been fully studied. The goal of this article is to propose and to evaluate a Bayesian method to estimate the GMMs with latent class dependent missing data. An extended GMM is first presented in which class…

This study estimates the high school dropout rate in rural and urban areas, the determinants of dropping out, and whether the differences in graduation rates have changed over time. We use geocoded data from two nationally representative panel household surveys (NLSY 97 and NLSY 79) and a novel methodology that corrects for biases in graduation…

Ever since achieving a high school credential by passing the GED[R] test became widely institutionalized through adult education programs in the United States, outcomes for GED test credential recipients have continued to be of great interest to the adult education community and the general public. Very few studies of GED test credential…

The purpose of this study was to predict occupational choices based on demographic variables and high school curriculum tracks. Based on an analysis of the 1997 National Longitudinal Survey of Youth (NLSY) data set that examined high school graduates' occupational choices in 2006, findings indicated that CTE graduates were 2.7 times more likely to…

Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data…

This Guide is an annotated bibliography of existing large scale data sets that provide useful information to policymakers, researchers, state administrators, and others in the field of child care and early education. The Guide follows an ecological approach to research and policy in the field: it brings attention not only to children themselves,…

A statistical analysis was performed to test the hypothesis that, if profit-maximizing firms have limited information about the general productivity of new workers, they may choose to use easily observable characteristics such as years of education to discriminate statistically among workers. Information about employer learning was obtained by…