Digital Module 16: Longitudinal Data Analysis

In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.     

Getting What You Pay For: Children's Use of Market Norms to Regulate Exchanges

Children are sensitive to a number of considerations influencing distributions of resources, including equality, equity, and reciprocity. We tested whether children use a specific type of reciprocity norm—market norms—in which resources are distributed differentially based strictly on amount offered in return. In two studies, 195 children 5–10 years and 60 adults distributed stickers to friends offering same or different amounts of money. Overall, participants distributed more equally when offers were the same and more unequally when offers were different. Although sensitive to why friends offered different amounts of money, children increasingly incorporated market norms into their distributions with age, as the oldest children and adults distributed more to those offering more, irrespective of the reasons provided.     

Social Perceptions of Students with Learning Disabilities Who Differ in Social Status

As a group, students with learning disabilities (LD) have social difficulties. One possible explanation for these difficulties is the unique way they process social information. Although students with LD may differ from their nondisabled peers in their social cognition, investigators have suggested the presence of subgroups within the population of students with LD who may differ in their social competence and, thereby, shed light on the source of the difficulties. The present exploratory study examined how two subgroups of students with LD in inclusive settings, students with high and low social status, perceive social situations. Using a sociometric technique, three students with LD receiving high social‐status ratings and three students with LD receiving low social‐status ratings were identified. A qualitative approach was used to gather and evaluate data from the participants and their teachers. Results suggested differences between the two subgroups in their (1) sensitivity to cues in the environment, (2) interpretation of social situations in relation to their own experiences, and (3) levels of self‐control. Implications of these findings for practice and future research are discussed.