Investigation of Two Preliminary Analysis-Altering Elements: Ordinate Scaling and DPPXYR.

The purpose of this pre-registered study (Peltier & McKenna) was to conceptually replicate if the truncation of the ordinate and DPPXYR increased analysts' estimation of a functional relation and magnitude of treatment effect. Visual analysts (n = 27) evaluated eight data sets reporting null (n = 2), small (n = 2), moderate (n = 2), and large (n = 2) effects. Each data set was graphed six times with manipulations of the ordinate and DPPXYR, resulting in 48 ABAB graphs. We estimated two separate three-level mixed effect models with variations nested in datasets and nested in participants to evaluate the impact of graph characteristics for (1) confidence in determining a functional relation and (2) the estimated magnitude of the treatment effect. We included ordinate scaling and DPPXYR at level 1 and graph effect size at level 2, including all interactions. Overall, graph manipulation consistently did not impact confidence in a functional relation. Results suggest mixed findings for graph manipulation on the estimated magnitude of the treatment effect. Findings will be couched in current literature and recommendations for graph construction and future research will be discussed.

Structured visual analysis of single-case experimental design data: Developments and technological advancements.

Visual analysis is the primary method used to interpret single-case experimental design (SCED) data in applied behavior analysis. Research shows that agreement between visual analysts can be suboptimal at times. To address the inconsistent interpretations of SCED data, recent structured visual-analysis technological advancements have been developed. To assess the extent to which structured visual analysis is used to guide or supplement applied behavior analysts' interpretation of SCED graphs, a systematic review between the years of 2015 to 2020 in the Journal of Applied Behavior Analysis was conducted. Findings showed that despite recent efforts to develop structured visual-analysis tools and criteria, these methods are rarely used to analyze SCED data. An overview of structured visual-analysis tools is shared, their utility is delineated, common characteristics are brought to light, and future directions for both research and their clinical use are highlighted.

A Decade Review of Two Potential Analysis Altering Variables in Graph Construction.

In single-case research designs (SCDs) to determine a functional relation a time-series graph is constructed. Preliminary evidence suggest the approach used to scale the vertical axis and the data points per x- to y-axis ratio (DPPXYR) impact visual analysts' decisions. We conducted a systematic review to evaluate time-series graphs published in the last decade in four premier journals in the field of autism. We included 348 articles including 2675 graphs. We identified large variation across and within types of SCDs when evaluating the lengths of the vertical and horizontal axis using the y:x ratio and the DPPXYR, with few adhering to current recommendations. A majority of graphs used an appropriate method to scale the vertical axis that would not increase Type I error rates.

Meta-analyses and effect sizes in applied behavior analysis: A review and discussion.

For more than four decades, researchers have used meta-analyses to synthesize data from multiple experimental studies often to draw conclusions that are not supported by individual studies. More recently, single-case experimental design (SCED) researchers have adopted meta-analysis techniques to answer research questions with data gleaned from SCED experiments. Meta-analyses enable researchers to answer questions regarding intervention efficacy, generality, and condition boundaries. Here we discuss meta-analysis techniques, the rationale for their adaptation with SCED studies, and current indices used to quantify the effect of SCED data in applied behavior analysis.

Using conceptual change theory to help preservice teachers understand dyslexia.

Recently, many states passed laws requiring pre- and in-service teachers to receive professional development in dyslexia awareness. Even though misconceptions regarding dyslexia are widespread, there is a paucity of research on how to effectively remove misconceptions and replace them with accurate knowledge. The purpose of this study was to determine whether a researcher-created refutation text grounded in conceptual change theory could produce significant conceptual change in preservice teacher knowledge of dyslexia when compared with a control text about dyslexia (Dyslexia Basics, International Dyslexia Association; IDA, 2018). A sample of preservice teachers (n = 97) was randomly assigned to either the Dyslexia Basics text (n = 48) or the refutation text (n = 49). A one-way repeated ANOVA was used to identify if growth rates from pretest to posttest were differential across conditions. Results suggest that while both texts affect conceptions, the refutation text outperformed the Dyslexia Basics text (n = 97), η2 = 0.33. Effects were maintained at a delayed posttest (n = 75), η2 = 0.175. Interaction effects suggested that the amount of reading coursework did not moderate conceptual change. Implications for facilitating conceptual change of dyslexia will be discussed.

Results reporting in single case experiments and single case meta-analysis.

Single Case Experimental Design is a discipline grounded in applied behavior analysis where the needs of individual clients and the application of scientific inquiry are fundamental tenets. These two principles remain tantamount in the conduct of research using this methodology and the expansion of the method into evidence-based practice determinations. Although recommendations for quality indicators are widespread, implementation is not. Concurrent to the rise of quality indicators is an increasing interest in analysis methodology. Visual analysis has a history of application and validity, newer forms of analysis less so. While some argue for concordance between the two, it may be the differences that are worth exploration in understanding characteristics of trend and variability in much of the published literature. Design choice and visual analysis decisions are rarely fully articulated. Statistical analyses are likewise inadequately justified or described. Recommendations for the explicit language of reporting as derived from prior meta-analysis and a current review of two leading journals provides a scaffold consistent with existing guidelines but additive in detail, exemplars, and justification. This is intended to improve reporting of results for individual studies and their potential use in future meta-analytic work.