This study investigated the relationship between children's mathematics performance and physical health using data from the Early Childhood Longitudinal Study Kindergarten Class of 2010-2011 (ECLS-K 2011). A two-level hierarchical growth curve model was used to explore the relationships between childhood mathematics performance and childhood…

Using data from the Early Childhood Longitudinal Study--Kindergarten Class of 2011 (n = 14,370; 51% Male; 51% White; 14% Black; 25% Hispanic; 4% Asian; and 6% Other), this study examined the cumulative, timing-specific, and enduring associations between student-teacher relationships in the United States and a broad range of student outcomes.…

Piecewise latent growth modeling (PLGM) is a class of longitudinal models using a structural equation modeling framework to describe stage-like, discontinuous change of individuals over time. PLGM breaks the overall time window into non-overlapped segments where separate functions can be fitted to represent differential growth patterns for each…

This study proposes transformation functions and matrices between coefficients in the original and reparameterized parameter spaces for an existing linear-linear piecewise model to derive the interpretable coefficients directly related to the underlying change pattern. Additionally, the study extends the existing model to allow individual…

Due to shifts in society's attitudes toward special education and changes in U.S. federal policies, such as the Individuals with Disabilities Education Act and No Child Left Behind, more students with disabilities (SWDs) are beginning kindergarten in general education classrooms. As a result, schools and districts across the United States have…

Nonresponse bias is a widely prevalent problem for data on education. We develop a ten-step exemplar to guide nonresponse bias analysis (NRBA) in cross-sectional studies and apply these steps to the Early Childhood Longitudinal Study, Kindergarten Class of 2010-2011. A key step is the construction of indices of nonresponse bias based on proxy…

The relation between reading and mathematics achievement is an active area of research, and evidence in the extant literature suggests they are closely related. However, there is a lack of understanding about how their relation develops over time. Indeed, traditional longitudinal analyses have focused on investigating each domain independently,…

Despite evidence of the benefits of early care and education (ECE) for child development and family employment, the supply of providers is scarce and variable; leading many families with young children to experience limited and inequitable access. To examine the multidetermined nature of access, this study leverages a multidimensional,…

As linguistic diversity continues to increase in the United States public school system, schools are expected to meet the needs of their ever-changing student body. While much attention within education research has understandably focused on multilingual learners' (MLs) English language acquisition, an emergent body of work points to science as an…

Student absenteeism in the earliest years of elementary school has been linked to a range of negative outcomes. Though the literature has examined numerous factors that are associated with children missing school, the role of teachers--especially at the early elementary level--has not been well understood. Given that students spend the majority of…

This study contributes to a growing body of scholarship at the intersection of bilingual education and education policy and examines reclassification, or the transition out of formal English language services in schools, as one potential lever in accelerating or decelerating multilingual learners' science learning. More specifically, it traces…

This study examined the longitudinal changes in kindergarten demographics and child outcomes by comparing data from the Early Childhood Longitudinal Survey (ECLS-K) 1998 and 2011 cohorts. Results demonstrated that there were significant changes in kindergarten in general and with regard to FDK and HDK schedules between 1998 and 2011. These…

Purpose: With rising numbers of deportations over the last 2 decades, there has been a particular concern among educators and researchers that immigrant-origin students and their peers are experiencing educational consequences due to increased stress, anxiety, and fear of the unknown. This study examined the relationship between immigration…

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…

When using multiple imputation, users often want to know how many imputations they need. An old answer is that 2-10 imputations usually suffice, but this recommendation only addresses the efficiency of point estimates. You may need more imputations if, in addition to efficient point estimates, you also want standard error (SE) estimates that would…