Table 5 Parameter estimation of MGWR-SAR
From: Spatial effects of public health laboratory emergency testing institutions under COVID-19 in China
| Â | Â | MGWR-SAR coefficient | Percentage of cities by significance (90% level) | ||||
|---|---|---|---|---|---|---|---|
Variable | Bandwidth | Mean | Min | Max | P ≤ 0.1 (%) |  + (%) |  − (%) |
Intercept term | 55.000 | -0.020 | -0.603 | 0.516 | 57.418 | 51.196 | 48.804 |
City level | 85.000 | 0.047 | -0.300 | 0.416 | 85.440 | 49.839 | 50.161 |
GDP per capital | 277.000 | -0.006 | -0.075 | 0.032 | 0.000 | 0.000 | 0.000 |
Population density | 45.000 | 0.654 | -0.027 | 1.700 | 78.022 | 100.000 | 0.000 |
Urbanization rate | 307.000 | -0.022 | -0.051 | 0.002 | 0.000 | 0.000 | 0.000 |
Number of medical colleges | 72.000 | 0.085 | -0.274 | 0.705 | 20.055 | 98.630 | 1.370 |
Altitude | 363.000 | -0.054 | -0.073 | -0.053 | 0.824 | 0.000 | 100.000 |
Casecount | 277.000 | -0.008 | -0.149 | 0.017 | 0.000 | 0.000 | 0.000 |
Outbreaks | 353.000 | 0.062 | 0.056 | 0.123 | 99.451 | 100.000 | 0.000 |
Number of tertiary hospitals | 98.000 | 0.276 | -0.051 | 0.561 | 69.505 | 95.257 | 4.743 |
Lag | 89.000 | 0.176 | -0.035 | 0.399 | 73.626 | 80.970 | 19.030 |