Visual analysis of data in a multielement design

Diller, James W.; Barry, Robert J.; Gelino, Brett W.

doi:10.1002/jaba.325

Cited by 21 publications

(31 citation statements)

References 6 publications

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“…Another benefit of including nonparametric statistical judgment aids in behavior analytic research is that it may promote wider acceptance of applied behavior analysis across other scientific disciplines (e.g., education, psychology, and neuroscience) where researchers may not be familiar with visual analysis. Although previous research has found that visual analysis of single‐subject graphs can be reliable (e.g., Diller, Barry, & Gelino, ; Kahng et al, ; Wolfe, Seaman, & Drasgow, ), the same research has observed a reduction in visual analysis reliability as a function of decreased rater experience and increased data complexity (Diller et al, ). In this connection, the supplemental information generated by ANSA, combined with standardized guidelines, can support the data interpretation process for behavior analytic students and practitioners who are gaining fluency in visual analysis.…”

Section: Discussionmentioning

confidence: 94%

Interpreting functional analysis outcomes using automated nonparametric statistical analysis

Hall

Pollard

Monlux

et al. 2020

J of App Behav Analysis

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Current methods employed to interpret functional analysis data include visual analysis and post‐hoc visual inspection (PHVI). However, these methods may be biased by dataset complexity, hand calculations, and rater experience. We examined whether an automated approach using nonparametric rank‐based statistics could increase the accuracy and efficiency of functional analysis data interpretation. We applied Automated Nonparametric Statistical Analysis (ANSA) to a sample of 65 published functional analyses for which additional experimental evidence was available to verify behavior function. Results showed that exact behavior function agreement between ANSA and the publications authors was 83.1%, exact agreement between ANSA and PHVI was 75.4%, and exact agreement across all 3 methods was 64.6%. These preliminary findings suggest that ANSA has the potential to support the data interpretation process. A web application that incorporates the calculations and rules utilized by ANSA is accessible at https://ansa.shinyapps.io/ansa/

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Section: Discussionmentioning

confidence: 94%

Interpreting functional analysis outcomes using automated nonparametric statistical analysis

Hall

Pollard

Monlux

et al. 2020

J of App Behav Analysis

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“…Unlike other fields (e.g., psychology) that rely on statistical comparisons and the standardization of collected data, behavior analysts rely almost exclusively on the visual inspection of summarized and plotted data over time. An extensive line of research has suggested that teaching visual analysis of graphs using standard didactic approaches and traditional supervisory methods might not lead to the development of fluent and reliable visual analytic repertoires in practicing behavior analysts (Danov & Symons, ; DeProspero & Cohen, ; Diller et al, ; Ninci, Vannest, Willson, & Zhang, ; Ottenbacher, ; Wolfe et al, ). However, a few studies have shown that when participants are directly taught specific visual analysis rules, agreement across participants improved (Hagopian et al, ; Roane, Fisher, Kelley, Mevers, & Bouxsein, ).…”

Section: Introductionmentioning

confidence: 99%

Using equivalence‐based instruction to teach the visual analysis of graphs

Blair

Tarbox

Albright

et al. 2019

Behavioral Interventions

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Previous research has demonstrated low rater agreement when visually inspecting trends in single‐subject design graphs (see Wolfe, Seaman, & Drasgow, 2016). Didactic instruction of visual analysis of practicing behavior analysts has resulted in generally poor and unreliable performances (Danov & Symons, 2008; Diller, Barry, & Gelino, 2016). Therefore, a refined instructional technology to improve the reliability among behavior analysts is warranted. Developing research has focused on the application of equivalence‐based instruction (Brodsky & Fienup, 2018; Rehfeldt, 2011) for a variety of complex human behaviors. In the current study, equivalence‐based instruction was used to train four participants to identify functional relations displayed in five different classes of graphs. Training resulted in the formation of five equivalence classes by all participants consisting of three members (graph, functional relation rule, and functional relation statement). In addition, the skills were maintained for up to 2 weeks and generalized to novel graphs.

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“…First, invoking visual inspection is not invariably straightforward. Often, naïve and well‐experienced researchers in behavior analysis do not reliably invoke visual inspection criteria or selectively invoke some criteria for their conclusions but ignore others (e.g., Diller et al, 2016; Ninci et al, 2015; Normand & Bailey, 2006; Wolfe et al, 2016). In addition, the different criteria, such as those provided in Table 2, do not always lead to the same conclusion.…”

Section: Single‐case Experimental Designsmentioning

confidence: 99%

Single‐case experimental designs: Characteristics, changes, and challenges

Kazdin

2020

J Exper Analysis Behavior

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Tactics of Scientific Research (Sidman, 1960) provides a visionary treatise on single‐case designs, their scientific underpinnings, and their critical role in understanding behavior. Since the foundational base was provided, single‐case designs have proliferated especially in areas of application where they have been used to evaluate interventions with an extraordinary range of clients, settings, and target foci. This article highlights core features of single‐case experimental designs, how key and ancillary features of the designs have evolved, the special strengths of the designs, and challenges that have impeded their integration in many areas where their contributions are sorely needed. The article ends by placing the methodological approach in the context of other research traditions. In this way, the discussion moves from the specific designs toward foundations and philosophy of science issues in keeping with the strengths of the person and book we are honoring.

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Visual analysis of data in a multielement design

Cited by 21 publications

References 6 publications

Interpreting functional analysis outcomes using automated nonparametric statistical analysis

Interpreting functional analysis outcomes using automated nonparametric statistical analysis

Using equivalence‐based instruction to teach the visual analysis of graphs

Single‐case experimental designs: Characteristics, changes, and challenges

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