Table 6.

The random effects estimates (b-values) for Algorithm Type 1 participants that had estimates that deviated significantly from the overall model estimates. The mixed effects model included log h-value entered as an intercept and slope parameter for both fixed and random effects determination. For the fixed effects, the intercept indicated that participants had a strong bias for certainty (CS preference) at the middle h-value, t(2846) = −14.26, p < .001, b = −6.51, [−7.40, −5.61]. UL choices increased significantly overall as a function of log h-value, t(2846) = 13.83, p < .001, b = 2.49, [2.14, 2.84]. The b-values for the individuals are the random effects estimates, with positive intercepts indicating more UL preferring and negative intercepts indicating more CS preferring (0 indicates indifference). Higher positive slopes indicate steeper discounting functions, and negative values indicate decreasing discounting functions. Significant (p < .05) deviations from the overall intercept (−6.51) and slope (2.49) are indicated in bold text and non-significant deviations are indicated in italics.

Participant	Intercept	Slope
8	0.79	−0.09
11	−4.52	1.27
31	−0.85	−0.15
35	−1.50	−0.12
37	−2.91	−0.11
45	−1.86	−0.26
48	−1.60	0.77
51	−4.83	1.22
54	−1.99	0.46
58	−0.42	0.90
63	−2.07	1.39
67	−0.10	0.86
84	−1.47	0.98
87	−2.97	0.88
88	−0.47	0.21
91	−2.69	1.79
94	−1.55	0.50
102	−0.60	0.15