Systematic Use of Visual Analysis for Assessing Outcomes in Single Case Design Studies

Abstract

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.

Power of a randomization test in a single case multiple baseline AB design

“…Visual inspection analysis offers a wide range of possibilities to investigate the patterns of individual time series and several measures have been developed to quantify this visual inspection (e.g. [18][19][20][21]). One may compare the means or medians of the observations in the baseline and intervention phase, or compare the range or standard deviation in the two phases.…”

Special Issue on Advances in Single-Case Research Design and Analysis

“…Researchers have sought to counter and directly address these criticisms by developing standardized protocols for assessing the credibility of single-case research design and evidence, 12,20,21 data analysis, reporting guidelines for publishing single-case research findings, 22 and the use of standardized visual analysis practices to determine the strength of the functional relation 23,24 and have validated training packages that can be used to train students and scholars in visual analysis. 14,25,26 For instance, the United States Department of Education Institute for Education Science (IES) White Paper defines the What Works Clearinghouse Pilot Standards for single-case design and analysis.…”

An exploration of the interrater agreement of visual analysis with and without context

“…When analyzing data from SCEDs to make decisions regarding intervention effectiveness, researchers most frequently turn toward visual analysis (Gast & Ledford, ). While flexible in nature, it is recommended that a visual analyst attend to (a) changes in level, (b) changes in trend or slope, (c) variability, (d) immediacy of the effect, (e) data overlaps across phases, and (f) consistency of data patterns across similar phases (Gast & Ledford, ; Ledford, Lane, & Severini, ; Parsonson & Baer, ). By evaluating these characteristics, researchers can determine the presence or absence of a functional relation and make decisions regarding intervention effectiveness (Kratochwill et al, ; Parsonson & Baer, ).…”