TITLE: A stochastic adventure in RT modeling: From random walks to nonlinear dynamics.
WHERE: Keats room, AVLG17, v/c to Ourimbah Science Offices.
ABSTRACT: In a broad summary of RT modeling since 1975, I first discuss the basic premises of Relative Judgment Theory and show how this relatively simple sequential sampling model can explain many important features of RT data in a variety of psychological contexts. Next I present a general nonstationary stochastic extension that includes the drift diffusion model and the Ornstein-Uhlenbeck model as special cases. I show how this complex model can be simplified by a tandem random walk decision process, which serves as a useful approximation for tasks involving brief stimuli. The talk concludes with evidence of nonlinear dynamics in sequential RT data using conventional techniques and multifractal spectra.
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