Open AccessGraphing the Intersection of Rate and Fidelity in Single-Case Research
Author(s) -
Melinda R. Snodgrass,
Hedda Meadan,
Moon Yong Chung,
Elizabeth E. Biggs
Publication year - 2021
Publication title -
behavior analysis in practice
Language(s) - English
Resource type - Journals
eISSN - 2196-8934
pISSN - 1998-1929
DOI - 10.1007/s40617-021-00556-w
Subject(s) - fidelity , computer science , intersection (aeronautics) , psychological intervention , graph , set (abstract data type) , machine learning , quality (philosophy) , multiple baseline design , intervention (counseling) , data science , psychology , artificial intelligence , data mining , theoretical computer science , engineering , telecommunications , philosophy , epistemology , psychiatry , programming language , aerospace engineering
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.