A growing body of literature has focused on missing data methods that factorize the joint distribution into a part representing the analysis model of interest and a part representing the distributions of the incomplete predictors. Relatively little is known about the utility of this method for multilevel models with interactive effects. This study…

Research has shown that mathematical proficiency gaps are related to students' and schools' indicators of poverty, with fewer studies on neighborhood effects on achievement gaps. Although this literature has accounted for students' nesting within schools, so far, methodological constraints have not allowed researchers to formally account for…

Specialized imputation routines for multilevel data are widely available in software packages, but these methods are generally not equipped to handle a wide range of complexities that are typical of behavioral science data. In particular, existing imputation schemes differ in their ability to handle random slopes, categorical variables,…

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

Learning analysts often consider whether learning processes across time are related (1) to one another or (2) to learning outcomes at higher levels. For example, are a group's temporal sequences of talk (e.g., correct evaluation [right arrow] correct, new idea) during its problem solving related to its group solution? I show how to address these…

Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

Education is a process by which man transmits his experiences, new findings, and values accumulated over the years, in his struggle for survival and development, through generations. Accordingly, one of the aims of education is to strengthen the individual's and societies' problem solving capacity, ability and culture starting from basic education…

This brief examined the patterns of reading achievement using statewide data from all students (Grades 3-10) in multiple years to examine gaps based on student, school, and district characteristics. Results indicate reading achievement varied most between students within schools and that students' prior achievement was the strongest predictor of…

The authors compared the effects of using the true Multilevel Latent Growth Curve Model (MLGCM) with single-level regular and design-based Latent Growth Curve Models (LGCM) with or without the higher-level predictor on various criterion variables for multilevel longitudinal data. They found that random effect estimates were biased when the…

This study investigated changes in reported test-taking motivation from a low-stakes to a high-stakes test and if there are differences in reported test-taking motivation between school classes. A questionnaire including scales assessing reported effort, expectancies, perceived importance, interest, and test anxiety was administered to a sample of…

In this study, we analyzed data for the Illinois high school class of 2003 to determine the impact of dual credit participation on postsecondary attainment. We matched 8,095 dual credit participants to an equal number of nonparticipants within the same high school at the point of postsecondary enrollment using propensity scores calculated through…

A challenge associated with traditional mixture regression models (MRMs), which rest on the assumption of normally distributed errors, is determining the number of unobserved groups. Specifically, even slight deviations from normality can lead to the detection of spurious classes. The current work aims to (a) examine how sensitive the commonly…

Longitudinal data analysis in education is the study growth over time. A longitudinal study is one in which repeated observations of the same variables are recorded for the same individuals over a period of time. This type of research is known by many names (e.g., time series analysis or repeated measures design), each of which can imply subtle…

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

Student enrollment in online courses has increased in the past 15 years and continues to grow. However, little is known about students' education experiences or online course outcomes. These are areas of particular interest to the Midwest Virtual Education Research Alliance, whose goal is to understand how to support student success in online…