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The implied imputation in SSBV-BLUP [ 11– 14] and the method presented here, only uses genotypes at the current locus.
Even with the choice of a rare-cutter enzyme, the threshold of less than 20% missing data that we applied to determine whether to keep a marker in the dataset led us to remove a large number of markers and implied imputation for the remaining scattered missing data.
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This is a special issue, as it implies imputation of the missing covariates and outcomes.
These results implied high imputation quality and comparable genotypes across the platforms.
However, in one case (rs2280788, CCL5) imputation implied an odds ratio (OR) of 0.75 when re-genotyping showed an effect size of 1.22.
The study also compared the proposed imputation approach with mean imputation and other three KNN imputation approaches.
The steps for multiple imputation involve: Imputation: This step involves the imputation of the missing values several times depending on the number of imputations stated.
We further observe that the importance of the imputed features in the learned classifiers is significant, implying that their imputation is important for prediction.
This is probably because of the qualitative imputation of D-dimer, and thus, the use of a multinomial imputation model, which implied estimation of parameters in separate strata defined by D-dimer concentration tertiles, some of which had a small number of events.
However, this does not imply that high imputation accuracy caused an increase in r GEBV.
Globally, the mean squared errors were smaller with MI than with the weighted estimator, with one exception implying a normal imputation model for a log-normally distributed phase-2 variable, an error which should easily be avoided.
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