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Table 3 Parameter estimates and 95% credible intervals for the joint model

From: Joint Bayesian modeling of time to malaria and mosquito abundance in Ethiopia

  Parameter Posterior mean 2.5% 97.5%
Abundance model     
Intercept β 0 0.18 -0.03 0.39
S 1(r a i n(t)) β 1 4.37 4.16 4.59
S 2(r a i n(t)) β 2 0.92 0.85 0.98
Measurement error σ 0.71 0.70 0.71
Time to event model     
Age θ 1 0.01 -0.03 0.05
Gender θ 2 -0.05 -0.22 0.12
Association main effect α 1 0.12 0.04 0.19
Association interaction α 2 0.26 0.16 0.36
Hyper-parameters     
Penalty λ 0.003 0.002 0.006
Random effect covariance D 1,1 23.55 22.15 25.05
Random effect covariance D 2,1 0.58 0.26 0.89
Random effect covariance D 3,1 -0.73 -0.99 -0.49
Random effect covariance D 2,2 2.16 2.01 2.31
Random effect covariance D 3,2 0.81 0.72 0.91
Random effect covariance D 3,3 1.42 1.32 1.52
DIC 403452.2
  1. D i,j denotes the ij-element of the covariance matrix for the random effects. We use a three week window to define the incidence I k(i)(t). In this run, the distance is not included in the model