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.     

Analyzing Food Science Research for Publishing Characteristics as a Model for Understanding the Needs of Researchers

Abstract

This paper provides a methodology to study the characteristics of the research output from a university department. The faculty publications and their cited references over a 10-year period were used as the basis for this study to identify their publishing patterns and the types of material they are publishing; a core set of journals and other resources they are publishing in and citing over this period; the characteristics of the journals in which they publish and cite; the degree of openness of their publications and their citation advantage; and the age of resources that are referenced.     

Effects of Manipulative Instruction on Solving Area and Perimeter Problems by Students with Learning Disabilities

Abstract. A multiple baseline design was employed to test the effect of manipulative instruction on the perimeter and area problem‐solving performance of middle and high school students who had been diagnosed with LD in the area of mathematics. Modeling, prompting/guided practice, and independent practice in conjunction with manipulative training were employed to teach both perimeter and area problem‐solving skills. Analysis of data revealed that the students rapidly acquired the problem‐solving‐skills, maintained these skills over a two‐month period, and transferred these skills to a paper and pencil problem‐solving format. This research extends previous findings by revealing that use of concrete manipulatives promotes the long‐term maintenance of skills.     

Social‐Information‐Processing Skills of Kindergarten Children with Developmental Learning Disabilities

The study examined the social‐information‐processing skills of kindergarten children with developmental learning disabilities (LD) utilizing Crick and Dodge's (1994) model of children's social adjustment as a theoretical framework. Participants consisted of 20 kindergarten children with developmental LD who attended three integrated kindergartens and 20 children without developmental LD from the same kindergartens. Participants were assessed on social‐information‐processing skills, feelings of loneliness, sense of coherence, and teachers' ratings of behavioral problems and positive resources. The results indicated that girls with developmental LD performed significantly lower on two information‐processing steps—the response decision and the enactment steps—than did girls without LD. Such differences were not found for boys. The results also showed that the social‐information‐processing skills of children with developmental LD were correlated with teachers' ratings.