Social network analysis (SNA) consists of a broad set of frameworks and methods to assess how direct and indirect relationships influence individual functioning. Although interest in SNA has steadily increased in the psychological sciences, school psychology has not kept pace. This article provides a general overview of core SNA concepts,…

Background: This paper considers a new policy and statistical framework for evaluating K-12 schools and policies that aligns with diversity, equity, and inclusion values. The new approach broadens the standard approach to accountability and evaluation by combining features of evaluation and multi-level growth models with approaches used in systems…

Researchers in the field of early adolescence interested in quantifying the environmental influences on a response variable of interest over time would use cluster sampling (i.e., obtaining repeated measures from students nested within classrooms and/or schools) to obtain the needed sample size. The resulting longitudinal data would be nested at…

Despite abundant anecdotes and theories suggesting a causal effect of teachers' expectations on student outcomes, documenting its presence and size has been challenging. The reason is simple: positive correlations between what teachers expect and what students ultimately accomplish might simply result from teachers being skilled observers. In…

Researchers, policymakers, and practitioners have recently aligned efforts to reduce school absenteeism, particularly during kindergarten when excessive absences are highest out of all elementary grades. Little is known, however, about whether the way in which students get to school might influence if they go to school. To address this gap, this…

Missing data (attrition and non-response) are a feature of most surveys especially longitudinal/panel studies. And many such studies now have multilevel designs and hence multilevel data structures. Recent advances in imputation methodology now offer social researchers opportunities to address issues of missing data in a statistically principled…

The multidimensional item response theory (MIRT) models with covariates proposed by Haberman and implemented in the "mirt" program provide a flexible way to analyze data based on item response theory. In this report, we discuss applications of the MIRT models with covariates to longitudinal test data to measure skill differences at the…

Established in December 2016, the National Academies of Sciences, Engineering, and Medicine's Roundtable on Data Science Postsecondary Education was charged with identifying the challenges of and highlighting best practices in postsecondary data science education. Convening quarterly for 3 years, representatives from academia, industry, and…

We utilized data from a multi-institutional longitudinal study to investigate the association between diversity-related coursework and moral development among students over 4 years of college. Our findings parallel the prior research, which support the positive effects of diversity on college students, by offering new evidence that diversity…

This study conducted secondary analysis of data from the National Longitudinal Transition Study-2 (NLTS2) to examine the degree to which student, family, and school constructs predicted self-determination outcomes. Multi-group structural equation modeling was used to examine predictive relationships between 5 student, 4 family, and 7 school…

This study conducted secondary analysis of data from the National Longitudinal Transition Study-2 (NLTS2) to examine the degree to which student, family, and school constructs predicted self-determination outcomes. Multi-group structural equation modeling was used to examine predictive relationships between 5 students, 4 family, and 7 school…

Studies based on longitudinal data focus on the change and development of the situation being investigated and allow for examining cases regarding education, individual development, cultural change, and socioeconomic improvement in time. However, as these studies require taking repeated measures in different time periods, they may include various…

Extensive research has conclusively demonstrated that children's social class is one of the most significant predictors--if not the single most significant predictor--of their educational success. This three-part study combines a statistical analysis of early skills gaps among a recent cohort of children and changes in them over time with a…

There are relatively few studies in Australia and South-East Asian region that combine investigating models of math growth trajectories with predictors such as reasoning ability and reading comprehension skills. Math achievement is one of the major components of overall academic achievement and it is important to determine what factors (especially…

Many higher education studies have examined linear relationships between student experiences and outcomes, but this assumption may be questionable. In two notable examples previous research that assumed a linear relationship reached different substantive conclusions and implications than did research that explored non-linear associations among the…