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

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

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

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.

ISSN: 1297-9686