Graphing the Intersection of Rate and Fidelity in Single-Case Research
Pick a graph that keeps rate and fidelity visible together so you never hide half the story.
01Research in Context
What this study did
Snodgrass et al. (2022) drew six new graph layouts. Each layout shows both rate and fidelity in one picture. The paper is a how-to guide, not an experiment.
The authors used made-up data to show when each layout works best. No clients were involved.
What they found
Some layouts hide fidelity when rate jumps. Others hide rate when fidelity dips. The paper tells you which layout keeps both stories clear.
How this fits with other research
Blair et al. (2022) shows how to build single-case graphs in free Google apps. Snodgrass gives you the blueprint; Blair gives you the hammer and nails.
Mitteer et al. (2022) uses Prism heat maps to spot fine-grain session detail. Snodgrass keeps rate and fidelity side-by-side instead of stacking them.
Tyrer et al. (2006) warned that visual calls can clash with stats. Snodgrass answers by making the picture itself easier to read, so the clash happens less.
Why it matters
If you graph only rate, you may miss that the intervention was done wrong. If you graph only fidelity, you may miss that the behavior barely changed. Pick one of the six formats, paste your data, and both messages stay visible to your supervisor, parent, or reviewer in one glance.
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02At a glance
03Original abstract
Single-case research is a prevalent and useful method for evaluating the effects of interventions in special education research. A single-case graph “should make available all of the data that permit evaluation of the criteria for visual inspection, at the very least,” while not misleading inspectors (Kazdin, 2011, p. 335). Although this is widely known, it poses challenges for multifaceted dependent variables, such as those that address both rate and a measure of quality, such as fidelity. Both factors may be important to accurately interpret intervention effects, such as those within cascading interventions implemented by natural change agents. However, representing both in a single graph is challenging. In response to this challenge, we present a single data set from a multiple-baseline design graphed in six distinct formats. Across these graphs, we discuss implications for visual analysis and interpretation and invite discussion of this important area of single-case research in search of recommendations for best practice.
Behavior Analysis in Practice, 2022 · doi:10.1007/s40617-021-00556-w