Comparison of probabilistic choice models in humans.
BACKGROUND
Probabilistic choice has been attracting attention in psychopharmacology and neuroeconomics. Several parametric models have been proposed for probabilistic choice; entropy model, Prelec's probability weight function, and hyperbola-like probability discounting functions.


METHODS
In order to examine (i) fitness of the probabilistic models to behavioral data, (ii) relationships between the parameters and psychological processes, e.g., aversion to possible non-gain in each probabilistic choice and aversion to unpredictability, we estimated the parameters and AICc (Akaike Information Criterion with small sample correction) of the probabilistic choice models by assessing the points of subjective equality at seven probability values (95%-5%). We examined both fitness of the models parametrized by utilizing AICc, and the relationships between the model parameters and equation-free parameter of aversion to possible non-gain.


RESULTS
Our results have shown that (i) the goodness of fitness for group data was [Entropy model>Prelec's function>General hyperbola>Simple hyperbola]; while Prelec's function best fitted individual data, (ii) aversion to possible non-gain and aversion to unpredictability are distinct psychological processes.


CONCLUSIONS
Entropy and Prelec models can be utilized in psychopharmacological and neuroeconomic studies of risky decision-making.
Takahashi
Taiki
T
Department of Life Sciences, Unit of Cognitive and Behavioral Sciences, School of Arts and Sciences, The University of Tokyo, 21 COE office, 3-8-1 Komaba, Meguro-ku, Tokyo, 153-8902, Japan. taikitakahashi@gmail.com
Oono
Hidemi
H
Radford
Mark H B
MH