Visual analysis of graphic displays of data is a cornerstone of studies using a single case experimental design (SCED). Data are graphed for each participant during a study with trend, level, and stability of data assessed within and between conditions. Reliable interpretations of effects of an intervention are dependent on researchers' understanding and use of systematic procedures. The purpose of this paper is to provide readers with a rationale for visual analysis of data when using a SCED, a step-by-step guide for conducting a visual analysis of graphed data, as well as to highlight considerations for persons interested in using visual analysis to evaluate an intervention, especially the importance of collecting reliability data for dependent measures and fidelity of implementation of study procedures.

The social and ecological validity of a body of research may impact the degree to which interventions will be used outside of research contexts. The purpose of this review was to determine the extent to which social and ecological validity were demonstrated for interventions designed to increase social skills for young children with autism spectrum disorders (ASD). Results indicated that although the percentage of studies including social validity assessment has remained stable over the 20-year review period, subjective assessments of social validity have increased and objective assessments have decreased. Acceptability was measured more often than feasibility or importance. Approximately half of the studies included indigenous implementers, typical social partners, or typical settings. Suggestions include additional research on the validity of measures, explicit reporting by researchers, and the use of multiple, objective, and psychometrically sound social validity assessments.

Single case designs (SCDs) allow researchers to objectively evaluate the impact of an intervention by repeatedly measuring a dependent variable across baseline and intervention conditions. Rooted in baseline logic, SCDs evaluate change over time, with each participant serving as his or her own control during the course of a study. Formative and summative evaluation of data is critical to determining causal relations. Visual analysis involves evaluation of level, trend, variability, consistency, overlap, and immediacy of effects within (baseline and intervention) and between conditions (baseline to intervention). The purpose of this paper is to highlight the process for visually analysing data collected in the context of a SCD and to provide structures and procedures for evaluating the six data characteristics of interest. A checklist with dichotomous responses (i.e., yes/no) is presented to facilitate implementation and reporting of systematic visual analysis.

We systematically reviewed more than 25 years of applied research examining the system of least prompts response prompting procedure with individuals with disabilities. We identified 123 peer-reviewed studies including 413 participants receiving instruction with the system of least prompts. A total of 252 experimental designs were evaluated, with 51 designs indicating a functional relation and the presence of 154 demonstrations of effect across 91 individuals. Our data indicate that the system of least prompts is an evidenced-based practice for teaching chained responses related to community, self-care, and vocational skills to individuals with moderate intellectual disability who are 13 years of age or older. In addition, we present and discuss a method for analyzing and aggregating data from single-case studies to account for noneffects and publication bias when identifying if an intervention meets standards as an evidence-based practice.

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