Description Usage Arguments References Examples
Function to simulate the predictions of the nROUSE model (Huber and O'Reilly, 2003; Reith & Huber, 2017) for perceptual identification latencies and forced-choice accuracy.
1 2 | simulate_nROUSE(presentations, primeInput, param = as.numeric(c(0.25, 0.0302,
0.15, 0.324, 0.022, 0.9844, 0.15, 1, 0.0294, 0.0609, 0.015)))
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presentations |
A vector giving the duration (in ms) of the prime, the target, the mask, and the choice alternatives. |
primeInput |
A vector of two elements used to set the type of prime. For instance, [2,0] indicates a double prime for targets, while [0,1] indicates a single prime for foils. |
param |
A vector giving the values for the parameters.
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Huber, D. E., & O'Reilly, R. C. (2003). Persistence and accommodation in short-term priming and other perceptual paradigms: Temporal segregation through synaptic depression. Cognitive Science, 27(3), 403-430.
Rieth, C. A., & Huber, D. E. (2017). Comparing different kinds of words and word-word relations to test an habituation model of priming. Cognitive Psychology, 95, 79-104. DOI: https://doi.org/10.1016/j.cogpsych.2017.04.002
1 2 3 4 5 6 | # Define duration (in ms) for prime, target, mask, and choices
presentations = c( 17, 50, 450, 500 )
# Set a double prime for targets
primeInput = c(2,0)
# Simulate model with default parameters
sim = simulate_nROUSE( presentations, primeInput )
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