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…

When selecting a multilevel model to fit to a dataset, it is important to choose both a model that best matches characteristics of the data's structure, but also to include the appropriate fixed and random effects parameters. For example, when researchers analyze clustered data (e.g., students nested within schools), the multilevel model can be…

This study proposes a new model, termed the multiple membership piecewise growth model (MM-PGM), to handle individual mobility across clusters frequently encountered in longitudinal studies, especially in educational research wherein some students could attend multiple schools during the course of the study. A real data set containing some…

This study is focused on the threat of retention associated with test-based promotion in Grade 3. Through analyzing the Early Childhood Longitudinal Study Kindergarten Class of 1998-1999 data, we found that schools having such a policy apparently increased math instructional time but not reading instructional time in Grade 3. On average, the…

We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases,…

School-average achievement is often reported to have positive effects on individual achievement (peer spillover effect). However, it is well established that school-average achievement has negative effects on academic self-concept (big-fish-little-pond effect [BFLPE]) and that academic self-concept and achievement are positively correlated and…

The purpose of this study was to examine the relationship between school-based kindergarten transition practices and student achievement and executive functioning using recent, nationally representative data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010-11. The analysis employed 3-level hierarchical linear models and…

There is considerable variation in state policies related to the certification required for teachers in kindergarten and first grade, and relatively little is known about these policies' effects on student learning. This study considers whether children who have kindergarten and first-grade teachers with certification in early childhood education…

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 study investigated how student and school-level socioeconomic status (SES) measures predict students' odds of being identified for special education, particularly high-incidence disabilities. Using the Early Childhood Longitudinal Study--Kindergarten cohort, hierarchical models were used to determine the relations of student and school SES to…

This study used ECLS-K 1998-1999 data to evaluate whether specific kindergarten teaching practices predicted school-year learning gains differently, depending on children's ethnicity, SES, and fall test scores. Exploratory factor analyses guided the creation of four literacy and five math instruction composites from teachers' reports of their…

Background/Context: Chronic school absenteeism is a pervasive problem across the US; in early education, it is most rampant in kindergarten and its consequences are particularly detrimental, often leading to poorer academic, behavioral and developmental outcomes later in life. Though prior empirical research has identified a broad range of…