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. 2022 Jun 30;13:617051. doi: 10.3389/fpsyg.2022.617051

Table 5.

Results of two-stage gambling experiments in literature and model fitting.

Literature p(again|win) p(again|lose) p(win) p(lose) p(again|unknown) θexpt θ1 θ2 θ3 θ4 θfit pfit
Tversky and Shafir, 1992 Experiment 1 0.69 0.57 0.5 0.5 0.38 113.49° 134.37° 146.22° 138.83° 139.59° 106.89° 0.45
Tversky and Shafir, 1992 Experiment 2 0.69 0.59 0.5 0.5 0.35 117.03° 134.64° 146.19° 138.32° 140.53° 106.91° 0.4
Tversky and Shafir, 1992 Experiment 3 0.71 0.56 0.5 0.5 0.84 71.03° 133.80° 147.43° 139.35° 139.02° 106.29° 0.46
Kühberger et al., 2001Experiment 1 0.6 0.47 0.5 0.5 0.47 97.03° 135.28° 142.49° 140.66° 136.54° 108.75° 0.36
Kühberger et al., 2001 Experiment 2 0.83 0.7 0.5 0.5 0.62 100.97° 133.41° 161.46° 137.71° 148.57° 99.27° 0.64
Kühberger et al., 2001 Experiment 3 0.8 0.37 0.5 0.5 0.43 106.55° 129.29° 153.45° 146.31° 131.19° 103.27° 0.46
Kühberger et al., 2001 Experiment 4 0.68 0.32 0.5 0.5 0.38 104.91° 131.30° 147.14° 147.14° 131.30° 106.43° 0.37
Lambdin and Burdsal, 2007 0.64 0.47 0.5 0.5 0.38 108.61° 134.24° 144.18° 141.11° 136.12° 107.91° 0.39
Surov et al., 2019 0.3 0.24 0.5 0.5 0.17 111.88° 147.53° 136.74° 152.19° 134.71° 111.63° 0.17

Columns 2–6 show the observed probabilities in the experiments. θexpt, θ1, θ2, θ3, and θ4 are the computed interference-phase differences of p(again|unknown), p(again|win), p(stop|win), p(again|lose), and p(stop|win), respectively, from observed probabilities. θfit is the fit value of θexpt by BIDM model. pfit is the p(again|unknown) fitted by BIDM model with θfit.