Evaluating sources of baseline data using dual‐criteria and conservative dual‐criteria methods: A quantitative analysis

Abstract

Scheithauer et al. (2020) recently demonstrated that differences in the source of baseline data extracted from a functional analysis (FA) may not affect subsequent clinical decision-making in comparison to a standard baseline. These outcomes warrant additional quantitative examination, as correspondence of visual analysis has sometimes been reported to be unreliable. In the current study, we quantified the occurrence of false positives within a dataset of FA and baseline data using the dual-criteria (DC) and conservative dual-criteria (CDC) methods. Results of this quantitative analysis suggest that false positives were more likely when using FA data (rather than original baseline data) as the initial treatment baseline. However, both sources of baseline data may have acceptably low levels of false positives for practical use. Overall, the findings provide preliminary quantitative support for the conclusion that determinations of effective treatment may be easily obtained using different sources of baseline data.

Discriminative stimuli promote the efficacy of delay tolerance training.

“…We opted for the former given (a) there was a relatively short time span between when baseline data were obtained and treatment initiated, (b) to reduce the time to treatment, and (c) prevent further reinforcement of problem behavior as a potential resurgence mitigation strategy (Fisher et al, 2022). To date, a handful of empirical studies indicate using data from previously conducted baseline conditions does not influence the reliability of clinical decision making (Falligant et al, 2020; Scheithauer et al, 2020). Nonetheless, additional research is needed to better understand the conditions under which discrepancies could occur.…”

Quantification of behavioral data with effect sizes and statistical significance tests

“…Skinner (1938) and Sidman (1960) emphasized experimental control with replicable methods and results over statistical analysis. However, quantitative approaches have been adopted and used in behavior analysis and behavior science at large (Becraft et al, 2020; Falligant et al, 2020; Gilroy et al, 2017; Kranak et al, 2021; Kyonka, 2019; Young, 2018; 2019) while experimental control and replication remains the most important area of emphasis (Hagopian, 2020; Kazdin, 2020). The addition of significance tests and effect sizes provides benefits for clinical decision‐making, communication across sciences, and allows for inclusion in systematic reviews, an area of growing importance and attention in single‐case research (see Dowdy et al, 2021; Manolov et al, 2017; Parker & Hagan‐Burke, 2007; Shadish et al, 2016).…”

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

“…Two methods of structured visual analysis with substantial research that are applicable to AB phase contrasts as part of a withdrawal design or multiple‐baseline design are the dual criterion (DC) and conservative dual criterion (CDC; Fisher et al, 2003; Wolfe et al, 2018) methods. Research suggests that both the DC and CDC methods effectively supplement visual analysis using simulated (Fisher et al, 2003; Stewart et al, 2007), published (Lanovaz et al, 2017; Wolfe et al, 2018), and unpublished clinical data sets (Falligant et al, 2019; Falligant, Kranak et al, 2020; Falligant, McNulty et al, 2020). That is, the accuracy with which differences across phases can be detected is improved when DC and CDC methods are employed, with CDC having evidence of a reduced Type I error rate in comparison to the DC.…”