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Missing data can be imputed via simple or multiple imputation methodology.
Although data can be imputed legitimately in some disciplines, it is generally frowned upon in clinical research, and this explanation came across as hollow and suspicious, especially since Poehlman appeared to have no idea how imputation was done.
If data are not missing in a systematic way, missing data can be imputed using the observed values for complete sets of observations as covariates for prediction purposes.
Von Hippel proposes that therefore the missing data can be imputed using the assumption that (Y, X, X) is jointly normally distributed (model (1)).
Missing values in ~omics data can be imputed by PhenoLink using a method supplied in the randomForest R package [ 18], though for this study we did not have missing values in the genotype data.
Because PEV is a reflection of the number and strength of the genetic relationships between individuals, it is expected to be a useful indicator for how well and individual's missing data can be imputed using all other individuals as a reference.
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When the data is sparsely sampled, as is often the case, additional data points can be imputed to bridge the gap between observations.
This confirms that the probability of missing values was unrelated to the value of any other variables in this study so that a single new data set that has no missing values can be imputed.
Data transformations such as taking logarithms may be appropriate and any missing values can be imputed using regression techniques.
The OCS-R loop can be imputed to the cable loop side, or the cable loop can be imputed to the OCS-R loop side.
For incorrectly imputed genotypes, either one or both alleles can be imputed incorrectly.
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