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. 2021 Jul 14;17(7):e1009129. doi: 10.1371/journal.pcbi.1009129

Table 1. Summary of epileptogenicity hypothesis testing using the classical and Bayesian information criteria (BIC/AIC/WAIC/LOO) in terms of deviance (-2 times log predictive density), penalty term, and Delta scores.

Here, three hypotheses as EZ, PZ, and HZ are evaluated on the excitability parameter of a selected brain region, where the ground truth is EZ. The smaller deviance and penalty terms, the smaller the value of information criterion, the better the model’s predictive ability. The correct hypothesis has a Delta score of zero.

Hypothesis
EZ PZ HZ
BIC -2logp(yθ^mle) 6435.83± 2.08 6437.77 ± 1.48 6438.70 ± 2.42
k (number of model parameters) 255 255 255
n (number of data points) 10080 10080 10080
BICi=-2logp(yθ^mle)+klog(n) 8786.49 ± 2.08 8788.44 ± 1.48 8789.37 ± 2.42
ΔBICi = BICi − BICmin 0.0 1.94 2.88
AIC -2logp(yθ^mle) 6435.83 ± 2.08 6437.774 ± 1.48 6438.70 ± 2.42
k (number of model parameters) 255 255 255
AICi=-2logp(yθ^mle)+2k 6945.83 ± 2.08 6947.77± 1.48 6948.70 ± 2.42
ΔAICi = AICi − AICmin 0.0 1.94 2.88
WAIC (Uninformative prior) −2lppdwaic 18053.88 ± 124.71 18071.15 ± 29.49 18140.93± 125.51
peff 3309.14 ± 277.61 3481.87 ± 431.05 3478.11 ± 501.51
WAICi = 2(lppdwaic − peff) 24672.17 ± 614.68 25034.89 ± 890.64 25097.17 ± 1109.20
ΔWAICi = WAICi − WAICmin 0.0 362.73 425.00
LOO (Uninformative prior) −2lppdloo 23693.80 ± 674.08 24036.58± 778.03 24143.98 ± 1136.79
LOOi = −2lppdloo 23693.80 ± 674.08 24036.58± 778.03 24143.98 ± 1136.79
ΔLOOi = LOOi − LOOmin 0.0 342.78 450.18
WAIC (Informative prior) −2lppdwaic 18051.38 ± 108.21 19477.37 ± 297.94 20958.32 ± 289.23
peff 3353.22 ± 236.12 4063.06 ± 86.26 4312.69 ± 64.99
WAICi = −2(lppdwaic − peff) 24757.83 ± 557.47 27603.50 ± 461.54 29583.71 ± 329.20
ΔWAICi = WAICi − WAICmin 0.0 2845.67 4825.88
LOO (Informative prior) −2lppdloo 23759.25 ± 332.94 27177.02 ± 609.29 29962.104 ± 343.11
LOOi = −2lppdloo 23759.25 ± 332.94 27177.02 ± 609.29 29962.104 ± 343.11
ΔLOOi = LOOi − LOOmin 0.0 3417.78 6202.85