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Code for running adaptive General Recognition Theory experiments

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JosephGlavan/Adaptive-GRT

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Adaptive-GRT

Repository of code, data, and analysis scripts for running Adaptive General Recognition Theory experiments (Glavan et al.)

Import the AGRT library to use the following classes and functions:

  • class AGRTHandler: PsychoPy handler object that initializes and manages the internal adaptive algorithm. Similar to PsychoPy's StairHandler.
  • class GRTHandler: PsychoPy handler object that implements the complete identification paradigm trial structure. Similar to PsychoPy's TrialHandler
  • function RunAdaptiveBlock: Creates an instance of AGRTHandler with the given parameters and runs the requested number of trials. Returns stimuli values corresponding to the requested level of accuracy.
  • function RunGRTBlock: Creates an instance of GRTHandler with the given parameters and runs the requested number of trials. Returns None.
  • function RunAdaptiveGRTExperiment: Uses the above functions to first run an adaptive block and then a main GRT block that uses the adapted stimuli.
  • function GRTSubjectModel: Example trial function used in the simulation study from Glavan et al.

Additional Files in this repository:

  • AGRT_Exp_x_x_x.py: Runs the human subjects experiments from Glavan et al.
  • AGRT Human Analysis.R: Analysis of the human subjects experiments from Glavan et al.
  • AGRT Quick Accuracy Check.R: Script that prints the accuracy of human subjects in the pilot condition. Used to inform the selection of stimuli.
  • test_simulation.py: Runs the simulation study from Glavan et al.
  • AGRT Python Simulation Study.R: Analysis of the simulation study from Glavan et al.

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