Background/Context: Predictive analytics has emerged as an indispensable tool in the education sector, offering insights that can improve student outcomes and inform more equitable policies (Friedler et al., 2019; Kleinberg et al., 2018). However, the widespread adoption of predictive models is hindered by several challenges, including the lack of…

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…

Multiple outcome recurrent event data are typical in social sciences, where several outcomes on an individual are collected. In situations where aggregated counts of events over a long observation period are recorded, rounding is common, leading to counts being heaped at rounded values. We consider situations where multiple outcome recurrent event…

Applied educational researchers may be interested in exploring random slope effects in multilevel models, such as when examining individual growth trajectories with longitudinal data. Random slopes are effects for which the slope of an individual-level coefficient varies depending on group membership, however these effects can be difficult to…

Machine learning (ML) methods for causal inference have gained popularity due to their flexibility to predict the outcome model and the propensity score. In this article, we provide a within-group approach for ML-based causal inference methods in order to robustly estimate average treatment effects in multilevel studies when there is cluster-level…

Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching…

The chemistry teacher pipeline has experienced considerable loss of teachers due to turnover. High turnover rates create localized staffing problems and a revolving door of novice teachers, particularly in the sciences and in urban and rural locales, which impacts student learning and achievement. This non-experimental longitudinal study examined…

This study explored the transition from secondary to postsecondary education among a national sample of students who had or had not studied music in high school. Using evidence from the High School Longitudinal Study of 2009, a nationally representative longitudinal study of 21,440 American high school students who were ninth graders in the…

Organized sports are among the most common youth activities in the United States, and athletic coaches can often become important mentors to their players. Nonetheless, few studies have examined the characteristics of youth who form mentoring relationships with coaches and whether such relationships are associated with later academic outcomes.…

Based on the Fragile Families and Child Wellbeing Study Year-5 wave, 1,983 children were identified as Head Start eligible children (503 Head Start enrolled children, 1,435 Head Start eligible nonparticipant) to address: (1) How do child and family characteristics differ between Head Start participants and non-participants? (2) How do Head…

This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare…

When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allow efficient and accurate estimation of multilevel IRT models, we argue that a two-stage…

Parametric methods, such as autoregressive models or latent growth modeling, are usually inflexible to model the dependence and nonlinear effects among the changes of latent traits whenever the time gap is irregular and the recorded time points are individually varying. Often in practice, the growth trend of latent traits is subject to certain…

In the context of cross-sectional surveys, the scope of research on the impact of response enhancing strategies on sample composition and nonresponse bias is vast. This topic has rarely been addressed for panel studies, however, although these are becoming an increasingly important data source in social research. In this article, we evaluate the…

Background: Few studies have examined associations of public library use and shared book reading to kindergarten children's academic skills. Methods: The study sample consisted of 13,385 kindergarten students enrolled in the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011 (ECLS-K: 2011). Parents reported on public library use…