Table 2 Parameter estimations of the computational learning model

From: Asymmetric cognitive learning mechanisms underlying the persistence of intergroup bias

Variable

Mean

Median

sd

rhat

89% HDI

Prior_In

–0.87

–0.87

1.17

1.0005

[–2.76, 0.98]

Prior_Out

–0.12

–0.13

1.17

1.0005

[–1.99, 1.76]

LR_Zap_In

0.71

0.70

0.84

1.0016

[0.27, 1.00]

LR_Zap_Out

0.84

0.82

0.78

1.0009

[0.55, 1.00]

LR_Avoid_In

0.08

0.07

0.85

1.0020

[0.00, 0.42]

LR_Avoid_Out

0.13

0.13

0.69

1.0000

[0.02, 0.27]

Bias

–1.01

–1.01

1.17

1.0005

[–2.86, 0.90]

w_dist_star

0.03

0.03

0.02

1.0001

[–0.04, 0.58]

w_dist_Target

–0.18

–0.18

0.02

0.9998

[–2.23, –1.46]

w_zap_Target

0.89

0.88

0.23

1.0007

[0.53, 1.22]

At_Zap_In

0.19

0.19

0.83

1.0004

[0.00, 0.60]

At_Zap_Out

0.22

0.22

0.75

1.0009

[0.01, 0.48]

At_Avoid_In

0.14

0.13

0.80

1.0008

[0.00, 0.44]

At_Avoid_Out

0.02

0.03

0.73

1.0004

[0.00, 0.06]

  1. Mean, median and standard error (sd) of the posterior distribution of group level parameters is presented, along with the 89% HDI. Rhat represents the convergence of the mcmcm chain, with values close to 1 representing convergence.
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