Table 1.

Parameter estimates. Mean-variance (U₁). The mean parameter estimates of θ₁ ± s.d. of a mean-variance decision-maker obtained from the linear regression analysis of the subjects' indifference points (see figure 2). Mean-Variance (U₂). The mean parameter estimates of θ₂ ± s.d. (estimated using bootstrapping with 1000 repetitions) of a mean-variance decision-maker obtained using a maximum-likelihood analysis of a noisy decision-maker. Prospect theory. The mean parameter estimates of α ± s.d. and γ ± s.d. (estimated using bootstrapping with 1000 repetitions) of a prospect theory decision-maker obtained using a maximum-likelihood analysis of a noisy decision-maker.

	subject
	1	2	3	4	5	6	7	8	9	10	11	12	13	14
mean-variance (U1)
θ1	0.46	0.16	0.16	0.14	0.12	0.12	0.11	0.08	0.04	0.03	0.02	−0.05	−0.05	−0.2
±	0.18	0.03	0.02	0.02	0.03	0.03	0.04	0.03	0.01	0.04	0.05	0.03	0.04	0.06
mean-variance (U2)
θ2	0.43	0.18	0.22	0.25	0.27	0.13	0.16	0.13	0.19	0.1	0.06	−0.18	−0.07	−0.34
±	0.03	0.02	0.02	0.02	0.02	0.02	0.02	0.02	0.03	0.02	0.03	0.02	0.03	0.03
prospect theory
α	0.28	0.12	0.13	0.13	0.22	0.09	0.06	0.09	0.25	0.28	0.12	2.61	2.76	4.76
±	0.05	0.04	0.03	0.04	0.05	0.03	0.03	0.06	0.14	0.18	0.04	0.23	0.45	0.22
γ	0.54	1.28	1.45	0.94	0.76	1.67	1.59	2.31	0.88	0.93	2.05	1.22	3.87	1.71
±	0.1	0.14	0.13	0.1	0.08	0.31	0.21	0.26	0.11	0.12	0.17	0.15	0.24	0.08