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Table 5 Multiple logistic regression models using SRTM and ASTER DEMs

From: Topographic models for predicting malaria vector breeding habitats: potential tools for vector control managers

 

SRTM (AIC = 3959.3)

 

ASTER (AIC = 3972.7)

 

Coefficient

SE

Coefficient

SE

Intercept

−2.914 ***

0.7839

−1.913 ***

0.2379

Elevation

−0.00699 *

0.00278

−0.00841 ***

0.00223

Slope

−0.2255 ***

0.0371

−0.1215 ***

0.0204

Plane Curvature

−823.5 **

277.5

−324.9 ***

69.81

Profile Curvature

−1143 ***

270.6

90.81 *

44.88

CI

– a

 

0.02219 ***

0.00469

TWI

0.1455 **

0.05239

0.09635 ***

0.02249

TPI500

−1.043 ***

0.2743

−0.9155 ***

0.1526

TPI2000

0.3443 **

0.1047

– b

 
  1. a, CI was not entered to the SRTM model because of high correlation with TPI500.
  2. b, TPI2000 was not selected in the final ASTER model.
  3. Asterisks indicate levels of statistical significance (*, P < 0.05; **, P < 0.01; ***, P < 0.001).
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Parasites & Vectors

ISSN: 1756-3305

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