Table 2.

Model-averaged regression coefficients for the six predictors in modelnormRE, modelnormGO, and modelRRnormRE

PredictorΣω*EstimateC value
Total RE content4.98160.73 (0.51-0.87)
L1PA123.36−1990.70 (0.49-0.85)
DNA/MER1-type3.27860.70 (0.49-0.85)
AT-rich2.901700.74 (0.54-0.87)
MLT2A22.091340.66 (0.45-0.82)
MIRb1.89440.69 (0.47-0.84)
PredictorΣω*EstimateC value
L1PA122.00−1920.70 (0.50-0.85)
AT-rich2.001640.73 (0.53-0.87)
MER2B1.30−2320.64 (0.43-0.80)
L1P4a1.10−1300.67 (0.45-0.83)
FLAM-C0.90890.63 (0.42-0.79)
L1MC20.40−280.67 (0.45-0.83)
PredictorΣωEstimateC value
AT-rich2.971070.73 (0.53-0.87)
L1PA121.95−800.70 (0.50-0.85)
MER2B1.17−1340.64 (0.43-0.80)
L1P4a0.92−1330.67 (0.45-0.83)
L1MC20.71−720.67 (0.45-0.83)
MLT2A20.57380.66 (0.45-0.81)
  • *Σω shows the sum of Akaike weights for each predictor across all models that contain the predictor (%). This sum reflects the relative importance of the respective predictor and was used as selection criteria.

  • C value gives the area under the ROC curve as calculated for each single predictor (95% confidence intervals).

  • Total sum in resampled model. The estimates are defined as slopes of each predictor.