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. 2010 Apr 21;9:19. doi: 10.1186/1476-072X-9-19

Table 2.

Equations for biologically relevant candidate models containing only significant variables in ordinary least squares regression and the corresponding AICC and R2 when these models were fitted using a Geographically Weighted Regression model.

Model Description OLS regression equation for model GWR AICC
[AICmodel- AICbest model]*
GWR R2(adj R2)
radiation only Y = 240 - 6.50 RAD 18943.51
[172.91]
30.9% (29.9)

radiation with quadratic term Y = 1101 - 122 RAD + 3.83 RAD2 18913.39
[142.79]
32.5%(31.1)

Pollutant and confounders Y = 179 - .364 HRT_DS -1.477 UNEMPLOY + .00003CROP 18905.71
[135.11]
34.9%(32.4)

Radiation, confounders, and pollutant Prst = 823.62 - .275 HRT_DS -2 UNEMPLOY -2.6RAD+.00003CROP+2.6 RAD2 18876.93
[106.33]
37.1% (34.0)

radiation and confounders Y = 840.54 - .293HRT_DS -2.36 UNEMPLOY - 83.54RAD + 2.63 RAD2 18868.70
[98.10]
36.0% (33.4)

HDD and confounders Y = 170 - 0.234 HRT_DS - 1.84 UNEMPLOY - 0.00550 HDD + 0.000002 HDD2 18843.07
[72.47]
36.4%(33.9)

Meteorological parameters without radiation but with confounders Y = 178.3 - .21 HRT_DS -1.77 UNEMPLOY - .006HDD + .027SNOW -0.085RAIN + 0.000002 HDD2 18812.07
[41.47]
39.0% (35.8)

Meteorological parameters including radiation and confounders Y = 467 - .193 HRT_DS - 1.83 UNEMPLOY -31.7RAD - .0094HDD - .16RAIN+.000002 HDD2
+.9 RAD2
18777.54
[6.94]
40.3% (36.8)

Meteorological parameters including radiation and pollutant and confounders Y = 470 - .193 HRT_DS -1.78 UNEMPLOY -34RAD - .009HDD + .00002CROP +.03SNOW - .116RAIN + .000002 HDD2 + 1 RAD2 18776.77
[6.17]
42.5%(38.1)

Meteorological parameters including radiation and pollutant and confounders and interactions Y = 460 - 0.198 HRT DS - 1.50 UNEMPLOY - 0.000010 CROP - 33.1 RAD - 0.00834 HDD + 0.0079 SNOW - 0.117 RAIN + 0.000002 HDD2 + 0.985 RAD2 + 0.00000046 CROP X SNOW 18770.60 43.3% (38.7)

* [Difference between the AIC of the model and the AIC of the best fit model. A number greater than 6 is considered significant [44]].