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Table 2 comparison of classical regression and GWR results

From: Variations in cardiovascular disease under-diagnosis in England: national cross-sectional spatial analysis

CHD Classical regression GWR
  O against E O = E+GP O against E O = E+GP
Residual sum of squares 0.032 0.026 0.026 0.017
Standard deviation 0.010 0.009 0.009 0.007
Akaike Information Criterion -2260.43 -2336.25 -2285.75 -2393.81
Correlation coefficient 0.299 0.439 0.427 0.637
Adjusted correlation coefficient 0.295 0.434 0.387 0.585
Sum of squares 0.0 0.0 0.0 0.0
Degrees of freedom 2.00 3.00 328.09 306.86
Hypertension Classical regression GWR
  O against E O = E+GP O against E O = E+GP
Residual sum of squares 0.374 0.250 0.362 0.241
Standard deviation 0.033 0.027 0.032 0.026
Akaike Information Criterion -1400.41 -1539.57 -1403.50 -1543.67
Correlation coefficient 0.121 0.412 0.150 0.432
Adjusted correlation coefficient 0.116 0.407 0.134 0.421
Sum of squares 0.4 0.2 0.4 0.2
Degrees of freedom 2.00 3.00 344.87 344.04
Stroke Classical regression GWR
  O against E O = E+GP O against E O = E+GP
Residual sum of squares 0.007 0.006 0.005 0.003
Standard deviation 0.004 0.004 0.004 0.003
Akaike Information Criterion -2807.25 -2873.16 -2838.92 -2932.93
Correlation coefficient 0.262 0.392 0.422 0.621
Adjusted correlation coefficient 0.258 0.387 0.374 0.561
  Classical regression GWR
  O against E O = E+GP O against E O = E+GP
Sum of squares 0.0 0.0 0.0 0.0
Degrees of freedom 2.00 3.00 324.37 302.87
  1. O against E: ratio of observed against expected prevalence
  2. O = E+GP: inclusion of GP supply as an additional independent variable