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Table 2 Variables selected by a Bayesian variable selection approach applied within the geostatistical logistic regression model

From: Spatio-temporal distribution of soil-transmitted helminth infections in Brazil

  A. lumbricoides infection T. trichiura infection Hookworm infection
Group 1    
Yearly mean temperaturea 0 0 0
Maximum temperature of warmest montha 0 0 0
Minimum temperature of coldest montha 0 0 0
Mean temperature of wettest quarter 0 0 0
Mean temperature of driest quarter 0 0 0
Mean temperature of warmest quartera x 0 x
Mean temperature of coldest quartera 0 x 0
Group 2    
Mean diurnal temperature rangeb x 0 0
Yearly temperature rangea,b 0 x x
Group 3    
Isothermality x x 0
Temperature seasonality 0 0 x
Group 4    
Yearly precipitationa x 0 0
Precipitation in wettest month 0 0 0
Precipitation in wettest quartera 0 x x
Group 5    
Precipitation in driest montha,c 0 x 0
Precipitation in driest quarterc x 0 x
Moderately correlated    
Precipitation seasonality x x x
Precipitation in warmest quarterb x x x
Precipitation in coldest quarterb,c x x x
Altitude x 0 x
Soil moisturea,b,c x 0 x
Soil pHb,c x x x
Human development index (HDI) x x x
Human influence indexb (HII) 0 x 0
Rural householdsb,c 0 x 0
Improved sanitation 0 0 0
Improved water supplya,b,c 0 0 0
Improved waste collectionb 0 0 0
Poor households x x 0
Survey period Fixed Fixed Fixed
Posterior probability (%) 44.8 93.5 25.3
  1. aCategorised for T. trichiura.
  2. bCategorised for hookworm.
  3. cCategorised for A. lumbricoides.
  4. x (selected), 0 (not selected).
  5. The best model selected by the geostatistical variable selections is presented for each soil-transmitted helminth species, together with its posterior probability.