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…

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…

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…

This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…

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…

Much is unknown about how initially high-achieving students grow academically, especially given the measurement issues inherent in assessing growth for the highest performing students. This study compared initially high-achieving and average students' growth in reading (in a cohort of third-grade students from 2,000 schools) over 3 years.…

The Simple View of Reading (SVR) describes Reading Comprehension as the product of distinct child-level variance in decoding (D) and linguistic comprehension (LC) component abilities. When used as a model for educational policy, distinct classroom-level influences of each of the components of the SVR model have been assumed, but have not yet been…

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…

Purpose: This study investigated cumulative effects of language learning, specifically whether prior vocabulary knowledge or special education status moderated the effects of academic vocabulary instruction in high-poverty schools. Method: Effects of a supplemental intervention targeting academic vocabulary in first through third grades were…

Policymakers view parental involvement (PI) as a crucial component of school reform efforts, but evidence of its effect on student achievement is equivocal. Using the Early Childhood Longitudinal Study-Kindergarten Cohort dataset, we examined the long-term impact on student- and school-level achievement of three types of school-based PI: PI to…