Applying Non-Parametric Adaptive Methods to Psychophysical and Simple Reaction Time Studies
Date Issued
2009
Date
2009
Author(s)
Chen, Yen-Ho
Abstract
In psychophysical research of detection and discrimination, non-parametric adaptive methods, including the fixed and non-fixed step-size methods, have been used extensively for the estimate of threshold through a combination of decreasing and increasing stimulus steps (see Leek, 2001; Treutwein, 1995, for reviews). In recent years, researchers have focused on the asymptotic and small-sample properties of some of those methods by simulations (e.g., Faes et al., 2007; García-Pérez, 1998, 2001).n this thesis I systematically investigate via simulations the asymptotic and small-sample properties of some of the non-parametric adaptive methods in two experimental situations, one concerns the yes-no detection task and the other the simple reaction time (RT) task. In particular, the application of adaptive methods for RT experiments provides an alternative to estimate signal intensities that elicit certain (fixed) RT percentiles. The convergences for different starting values, step sizes, and response criteria are systematically investigated in both tasks. The results show that the accelerated stochastic approximation (ASA) (Kesten, 1958) is suitable for both tasks. A fixed-step-size method called the biased coin design (BCD) (Durham & Flournoy, 1993, 1995) with small step sizes is also recommended. Furthermore, our simulation results show that for small sample sizes, it is also feasible to apply ASA first, then followed by BCD, as the combined method.
Subjects
accelerated stochastic approximation
biased coin design
detection
non-parametric adaptive method
simple reaction time
stochastic approximation
transformed up-down method
weighted up-down method
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