Abstract
Resurgence as Choice in Context (RaC2) is a quantitative model for evaluating the reemergence of a previously extinguished response when alternative reinforcement is worsened. Rooted in the matching law, RaC2 proposes that allocation between target and alternative responding is based on changes in the relative value of each response option over time, accounting for periods with and without alternative reinforcement. Given that practitioners and applied researchers may have limited experience with constructing quantitative models, we provide a step-by-step task analysis for building RaC2 using Microsoft Excel 2013. We also provide a few basic learning activities to help readers better understand RaC2 itself, the variables that affect the model’s predictions, and the clinical implications of those predictions.
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Data Availability
All data described in this study are included in this published article and its supplementary information files.
Notes
For more recent versions of Microsoft Excel (i.e., after 2016), the formulas and text will remain the same. However, there may be some differences in the steps required to complete certain tasks, such as formatting cells or inserting a graph. For additional guidance on how to access features on newer versions of Excel, please see https://support.microsoft.com.
For illustrative purposes, we opt to use VI schedules here for ease of predicting the total number of reinforcers per hour. Of course, this can also be done with other types of schedules (e.g., fixed-ratio, fixed-time) as well for both RaC and RaC2.
In real-world application, these parameters can be freely estimated via the Generalized Reduced Gradient (GRG) Nonlinear Solving Method (Lasdon et al., 1978) in the Solver Add-In for Microsoft Excel. For an overview of how to install and use the Solver Add-In to estimate free parameters in quantitative behavioral models, see Reed et al. (2012).
This template is for educational purposes only. Readers may need to modify the scale of the y-axis to facilitate visual inspection of the data series depending on specific parameter values and experimental arrangements used within this model.
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The authors acknowledge Jasmeen Kaur, Nathalie Fernandez, Brittney Workman, and Hailee Hall for their helpful feedback on prior drafts of this article. The authors also thank the anonymous reviewers with their invaluable feedback on the learning activities and template.
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Laureano, B., Falligant, J.M. Modeling Behavioral Persistence with Resurgence as Choice in Context (RaC2): A Tutorial. Behav Analysis Practice 16, 640–651 (2023). https://doi.org/10.1007/s40617-023-00796-y
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DOI: https://doi.org/10.1007/s40617-023-00796-y