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Table 3 Results from the Bayesian models with informative priors including different percentages of discrepant expert opinion

From: Prediction models for clustered data with informative priors for the random effects: a simulation study

  FREQ BAYES.WI BAYES.LI BAYES.MI BAYES.HI
Percentage wrong expert opinion 10% 30% 50% 10% 30% 50% 10% 30% 50%
Overall Brier score .191 .192 .180 .192 .201 .174 .179 .182 .170 .173 .174
Overall C-index/AUC .782 .781 .806 .781 .764 .818 .808 .801 .826 .821 .818
Overall calibration slope .911 .907 .946 .874 .824 .982 .964 .950 .989 .988 .987
Within cluster C-index/AUCa .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037] .805 [.037]
Within cluster calibration slopea .914 [.102] .914 [.102] .946 [.091] .939 [.100] .935 [.100] .953 [.077] .939 [.084] .935 [.085] .962 [.059] .953 [.068] .951 [.070]
  1. amean[sd]