Creating Single-Subject Research Design Graphs with Google Applications

Blair, Bryan; Mahoney, Paul J.

doi:10.1007/s40617-021-00604-5

Cited by 4 publications

(4 citation statements)

References 11 publications

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“…Paid licenses are also available with extra features like upgraded cloud storage at a slightly cheaper cost than Microsoft 365. Blair and Mahoney (2022) provided the first graphing tutorial for Sheets (Google, n.d.). However, similar to Excel, creating graphs of sufficient quality for publication may be time‐consuming.…”

Section: Graphing Programsmentioning

confidence: 99%

“…Providing readers with materials such as task analyses or video models is one way to facilitate the learning of SCED graphical creation by individuals beyond those participating in a study. Between 2017–2021, 5 of 11 graphing publications were tutorials only, with task analyses focused on teaching readers to use novel graphing software (e.g., Sheets; Blair & Mahoney, 2022; Google, n.d.) or novel procedures for existing programs (e.g., automated phase‐change lines; Deochand, 2017). These studies offer the training materials to readers who have access to the journal article, which is an enormous benefit to readers of those journals.…”

Section: Article Typementioning

confidence: 99%

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A concise review of recent advancements in the graphical training of behavior analysts

Kranak

Mitteer

2022

J of App Behav Analysis

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Section: Graphing Programsmentioning

confidence: 99%

Section: Article Typementioning

confidence: 99%

A concise review of recent advancements in the graphical training of behavior analysts

Kranak

Mitteer

2022

J of App Behav Analysis

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“…Graphing data, especially singlecase design data, is another critical skill for many professionals. Although tutorials for graphing such data have been available for over two decades (e.g., Blair & Mahoney, 2022;Carr & Burkholder, 1998;Deochand, 2017;Hillman & Miller, 2004;Moran & Hirschbine, 2002;Watts & Stenhoff, 2021), researchers have only recently evaluated the efficacy of similar tutorials as trainings in asynchronous formats (see for a review Kranak & Mitteer, 2022). Mitteer et al (2018) used video modeling as an asynchronous training to increase the accuracy of graphing in GraphPad Prism for four credentialed or prospective Registered Behavior Technicians (RBTs).…”

mentioning

confidence: 99%

The influence of measurement on interpreting accurate graphing during an asynchronous training.

Bernstein,

Dachman,

Romero

et al. 2024

Behavior Analysis: Research and Practice

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Asynchronous trainings can increase the accuracy of graphing single-case design data. Researchers, however, have measured accuracy using a permanent product when employing asynchronous trainings for graphing. Permanent product measures are insensitive to the graphing process (i.e., adherence to the training), steps of this process yielding intangible outcomes, and steps of this process yielding tangible outcomes that are indiscernible through viewing a final output. A continuous measure of accuracy would account for the graphing process better and further measure the efficacy of the training and the use of an asynchronous training modality overall. Professionals also create graphs at the inception of data collection such that these graphs update automatically with ongoing data entry. A continuous measure of accuracy could further highlight errors during specific steps of the graphing process for which professionals can intervene to mitigate uninterpretable or misinterpreted data likely to affect clinical programming. We replicated the efficacy of enhanced written instructions as an asynchronous training for graphing single-case design data for all seven participants. We evaluated accurate graphing using two permanent product measures from the existing literature and a novel, continuous measure. Both permanent product measures generally overestimated accuracy in the absence of training. We also present data on latency to graph completion, maintenance, and generalization before discussing the implications of measurement on interpreting the outcomes of asynchronous trainings.

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“…A very popular approach to visualizing causal structure are directed acyclic graphs (DAGs). However, it is notoriously difficult to encode time with DAGs.25 The term research design graphs has been used previously(Blair and Mahoney 2022;Kazdin and Tuma 1982).24 There is a discussion around whether this second part is necessary(Keele 2015).23 Because we administer the treatment, it is exogenous, and we do not have to worry about simultaneity bias resulting from reverse causation.22 As argued above an IRD is tied to the real-world and does not allow for observing potential outcomes as is the case in thought experiments.…”

mentioning

confidence: 99%

From ideal experiments to ideal research designs (IDRs): What they are and why we should use them more

Bauer¹,

Landesvatter²

2023

Preprint

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It is often recommended to investigate causal research questions by considering an ideal experiment. An ideal experiment describes the study a researcher would carry out without practical, ethical, or resource-related constraints (e.g., Angrist and Pischke 2008). First, we review whether and how methodologists define and advocate using ideal experiments (IEs). Second, we introduce the more general notion of ideal research designs (IRDs), discuss their components, and contrast them with actual research designs (ARDs). IRDs go beyond IEs in that they also speak to issues such as measurement errors that are rarely the focus of IEs. Third, we discuss an IRD and corresponding ARD to explain the various components of an IRD. Fourth, we introduce research design graphs (RDGs) which may be used to visualize and compare some essential components of IRDs/ARDs. Fifth, departing from our systematic account, we review applied examples of whether and how researchers have used IEs and IRDs in applied empirical research. While we find few examples, they attest to the usefulness of IRDs to benchmark actual research designs (ARDs) of previously realized or planned studies.

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Creating Single-Subject Research Design Graphs with Google Applications

Cited by 4 publications

References 11 publications

A concise review of recent advancements in the graphical training of behavior analysts

A concise review of recent advancements in the graphical training of behavior analysts

The influence of measurement on interpreting accurate graphing during an asynchronous training.

From ideal experiments to ideal research designs (IDRs): What they are and why we should use them more

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