# Table 1 An example of using posterior samples from model development data analysis for prediction in a new cluster

Posterior from model development data      Prediction for new cluster c
Iteration      Subject 1 Subject nc
k $${\overset{\sim }{\beta}}_0^{(k)}$$ $${\overset{\sim }{\beta}}_1^{(k)}$$ $${{\overset{\sim }{\sigma}}_u^2}^{(k)}$$ $${\widehat{u}}_c^{(k)}$$ a x 1 c $${\widehat{p}}_{1c}^{(k)}$$ b $${x}_{n_cc}$$ $${\widehat{p}}_{n_cc}^{(k)}$$ b
. . . . . . . . . .
. . . . . . . . . .
5001 −1.35 1.07 1.17 .50 1.11 .58 −.46 .21
5011 −1.24 1.08 .88 −1.89 1.11 .13 −.46 .03
5021 −1.36 1.18 1.28 −.06 1.11 .47 −.46 .12
5031 −1.31 1.05 .98 −.64 1.11 .31 −.46 .08
5041 −.94 .98 1.37 .26 1.11 .60 −.46 .24
. . . . . . . . . .
. . . . . . . . . .
Median       .52    .15
1. arandom effect sampled from the normal distribution $$N\left(0,{{\overset{\sim }{\sigma}}_u^2}^{(k)}\right)$$
2. bpredicted risk calculated by $${\widehat{p}}_{\mathrm{sc}}^{(k)}=\frac{1}{1+\exp \left(-{\overset{\sim }{\beta}}_0^{(k)}+{\overset{\sim }{\beta}}_1^{(k)}{x}_{sc}+{\widehat{u}}_c^{(k)}\right)}$$