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Table 4 Cross-validation summary statistics for each single-trait model for mastitis

From: Genomic prediction of disease occurrence using producer-recorded health data: a comparison of methods

Data without daughter restrictions
  AICC \(\sum \chi ^{2}\) WP
Pedigree-based -2.20 963462 0.109
BayesA -2.13 966992 0.110
Single-step -2.18 963280 0.111
Data with daughter restrictions
  AICC \(\sum \chi ^{2}\) WP
Pedigree-based -5.05 1846303 0.017
BayesA (non-weighted) -4.82 1934351 0.009
BayesA (weighted) -4.73 1839123 0.019
Single-step -5.03 1787162 0.033
  1. Corrected AIC (AICC) estimated via local weighted regression of average mastitis incidence per sire on EBV of sire for each model fit with the full dataset. Sum of χ 2 (\(\sum \chi ^{\text {2}}\)) is a measure of predictive ability, with smaller values being preferred. Median proportion of wrong predictions represented by WP.