Sentence examples for imputation uses from inspiring English sources

The sequential imputation uses samples and associated weights to approximate the unknown distribution in the presence of missing data, and thus can be seen as a combination of Gibbs sampler and sequential importance sampling.

Imputation uses correlations between nearby variants to help call genotypes.

For predicting untyped genotypes, imputation uses estimated haplotype segments from the reference panel for the overlapping variants between reference and genotype panels.

Multiple imputation uses multiple predictions of missing clinical endpoints based on patient characteristics and the baseline value of the clinical outcome variables [ 16].

Multiple imputation uses regression analysis to allow the correlations between the variables in the data set to be maintained when imputing.

The first exemplar imputation uses survey data from Cambodia: the Cambodia Socio-economic Survey (CSES) 2009, that is the source of the new national poverty line estimates, and the Demographic and Health Survey (DHS) 2010.

Missing covariate data were imputed with multiple imputation using IVEwareE [ 16].

These were imputed once with single imputation, using R software.

Missing data were imputed using MICE (multiple imputation using chained equations) [ 21].

11 Missing data was imputed by the method of multivariate imputation using chained equations.

Missing values in the possible determinants were imputed using the MICE technique (Multiple Imputation Using Chained Equations).