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Table 2 Results of the Bayesian logistic regression model.

From: Spatial prediction of malaria prevalence in an endemic area of Bangladesh

Variable Posterior distribution
  OR (95% CI)
Age* 0.95 (0.93,0.97)
Economic status (live with deficiency) 1
Economic status (Deficient sometimes) 1.11 (0.50, 2.14)
Economic status (No deficient nor surplus) 1.70 (0.78, 3.23)
Economic status (Surplus) 1.37 (0.52, 2.90)
Forest type (deep forest) 1
Forest type (fragmented forest) 1.82 (1.02, 3.16)
Forest type (other woodland) 1.16 (0.20, 3.46)
Elevation* 1.17 (0.90, 1.51)
Intercept 0.31 (0.13, 0.63)
Rate of decay of spatial correlation# 399 (147.8, 587.2)
Variance of spatial random effect 0.62 (0.03,2.39)
  1. *CI = Credible interval; SD standard deviation; Values for the fixed effects are odds ratios; note the odds ratios for age and elevation are on a common scale, where the variables were standardized to have a mean = 0 and standard deviation = 1. #in decimal degrees.