Addressing Challenges for Statistical Analysis in Small-Group Designs

• In Event: Poster Session 10
  In Poster Session: Division D Section 2 Poster Session 2

Abstract

Single case designs (SCD), studies with single participants or small N groups, pose various challenges to statistical analysis and, consequently, until recently, visual analysis has been the preferred approach for assessing treatment effects in such designs. However, advances in statistical methods have led to a renewed interest in alternatives to visual analysis of SCD, with a number of new proposals appearing in both education and neuropsychological research. This paper focuses on the approach of mixed-effects modeling with crossed random effects for both participants and items (Baayen et al., 2008), arguing that this class of regression models addresses the statistical pitfalls of ordinary least squares regression as applied to SCD, and provides an important alternative to visual analysis.

Authors

• Robert W Wiley, Johns Hopkins University

• Brenda Rapp, Johns Hopkins University