Sentence examples for approach for imputation from inspiring English sources

Given the fact that there exists a robust mtDNA worldwide phylogeny based on entire mtDNA genomes (>8,700), the phylogenetic-based approach for imputation seems more reliable than those based on e.g. metrics for linkage disequilibrium [29].

Another approach for imputation in African American populations has been recently suggested by Paşaniuc et al. (2011) [ 54].

Primary efficacy analyses were based on the ITT population and the LOCF approach for imputation of missing values.

Where there was missing data, a second analysis was performed used multiple imputation with 20 copies of the dataset and using a regression approach for imputation.

Good performance of the autosomal approach for imputation of sex chromosomes may be due to the pedigree haplotype library imputation step, which is independent of the mode of inheritance.

It is likely that RFI and kNNI produced comparable levels of accuracy because both use a similar model free approach for imputation that involves weighting a selected set of k important variables according to a distance metric (Lin and Jeon 2006).

To explore various approaches for imputation of untyped markers using a reference panel determined from sequencing data, we utilized a recently completed sequencing study for a gene which we will denote as GENE1 (unpublished data).

Different approaches for imputation of genotypes exploit pedigree information [ 12], population-wide LD (e. g. [ 13, 14]) or both sources of information (e. g. [ 15]).

We performed the complete cases analysis with all methods and used three different approaches for imputation of missing values: i) addition of a categorical variable encoding the presence of a missing value; ii) substitution with the overall population mode for binary attributes and mean for numeric ones; iii) non-linear imputation based on random forests [ 33].

MICE is a practical approach for imputing missing datasets based on a set of imputation models, given that there is one model for each variable with missing values.

The features from the mean-imputation unified dataset presented higher instability than all other methods and so proved to be the least preferable approach for the imputation procedure.