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…

Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…

Large-scale education data are collected via complex sampling designs that incorporate clustering and unequal probability of selection. Multilevel models are often utilized to account for clustering effects. The probability weighted approach (PWA) has been frequently used to deal with the unequal probability of selection. In this study, we examine…

Many national and international educational data collection programs offer researchers opportunities to investigate contextual effects related to student performance. In those programs, schools are often used in the first-stage sampling process and students are randomly drawn from selected schools. However, the "incidental" dependence of…

The Equality of Educational Opportunity Study (1966)--the Coleman Report--lodged a key takeaway in the minds of educators, researchers, and parents: Schools do not strongly shape students' achievement outcomes. This finding has been influential to the field; however, Coleman himself suggested that--had longitudinal data been available to…

Background: Observation Studies, Unmeasured Confounding, and Sensitivity Analysis: An important part of educational research is identifying important, potentially causal, factors that influence children's learning from observational studies. However, it is well-known that discovering such factors from observational studies can be biased due to…

Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…

Defining rural is a critical task for rural education researchers, as it has implications for all phases of a study. However, it is also a difficult task due to the many ways in which rural can be theoretically, conceptually, and empirically operationalized. This article provides researchers with specific guidance on important theoretical and…

Conventional multilevel modeling works well with purely hierarchical data; however, pure hierarchies rarely exist in real datasets. Applied researchers employ ad hoc procedures to create purely hierarchical data. For example, applied educational researchers either delete mobile participants' data from the analysis or identify the student only with…

This case study is directed at the methods used to examine group differences when random group assignment is not a feasible option. The authors discuss how to employ propensity score matching techniques and practical issues that arise when employing such techniques. The context of using propensity score matching is embedded in a research study…

The introduction to this Special Topic Collection has two parts. To provide background and context for the articles in the collection, Part 1 tells the story of the Early Childhood Longitudinal Study program at the National Center for Education Statistics. It offers an abridged history of this program and describes the designs of the two national…

Often it is infeasible or unethical to use random assignment in educational settings to study important constructs and questions. Hence, educational research often uses observational data, such as large-scale secondary data sets and state and school district data, and quasi-experimental designs. One method of reducing selection bias in estimations…

As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…

Forty years ago, the National Center for Education Statistics initiated the national longitudinal studies program in response to congressional concern for policy-relevant information on school-to-work transitions. This program has grown substantially, and not unexpectedly, questions have arisen about its usefulness and present operation. This…