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Table 5 Comparison of negative binomial, spatial lag, global and local geographically weighted Poisson models

From: Socioeconomic determinants of geographic disparities in campylobacteriosis risk: a comparison of global and local modeling approaches

  Model type with Coefficient estimates (p-values)
  Negative Binomial Model Spatial Lag Model Global Poisson GWR1 Model Local Poisson GWR1 Model
Model 1:     Min Max
Intercept −7.164 (0.0001) 1.716 (0.000) - 7.155 (0.000) −8.187 -6.247
Black Race −0.015 (0.0001) −0.169 (0.001) −0.014 (0.001) −0.0487 0.0218
No diploma 0.021 (0.0004) −0.012 (0.112) 0.003 (0.003) −0.0553 0.0533
Unemployed −0.041 (0.0141) −0.030 (0.112) −0.014 (0.009) −0.1866 0.0851
Urban 0.235 (0.0154) 0.357 (0.014) 0.186 (0.055) −0.4526 0.9321
Model 2:      
Intercept - 6.73 (0.0001) 1.80 (0.000) - 6.85 (0.000) −7.71 -4.905
Black Race −0.0129 (0.0001) −0.093 (0.000) −0.012 (0.001) −0.0161 0.0311
No diploma 0.0175 (0.0009) −0.018 (0.011) 0.000 (0.003) −0.0650 0.0882
Unemployed −0.0330 (0.0433) −0.026 (0.179) −0.010 (0.008) −0.1847 0.0752
Divorced −0.0260 (0.006) −0.004 (0.733) −0.016 (0.005) −0.2485 0.0382
  1. 1 Geographically Weighted Regression.