Sentence examples for multiple imputation algorithms from inspiring English sources

Convergence of the multiple imputation algorithms was usually achieved very soon, i.e. even less than ten iterations would have sufficed.

Therefore, multiple imputation algorithms were used to analyze the missing data using NORM software version 2.03 [ 27].

Although we are aware of benefits resulting from multiple imputation algorithms, we agreed on using the master data set for the sake of consistency and because the proportion of missing values in the variables used for our analysis was very small.

We first imputed the missing data using mice (multiple imputation algorithm), based on 30 multiple imputed datasets.

Missing exposure data were imputed with a multiple imputation algorithm (SAS MI procedure, version 9.2; SAS Institute Inc., Cary, NC) based on the exposure data for all eligible persons (n = 2,222), creating 18 replicate imputed data sets.

This guarantees that the multiple imputation algorithm produces a p-value close to 0 if all imputed data sets are highly unlikely under HWE, and a p-value close to 1 if all imputed data sets are highly likely under HWE.

FCS – FCS, also termed "chained equations", is the multiple imputation algorithm adopted by SPSS [ 21].

Finally, missing observations were imputed based on proximate years using a custom multiple-imputation algorithm [ 14].

Six methods of imputation were compared: 1) random selection, 2) preceding question, 3) question mean, 4) individual mean 5) single regression and 6) a multiple imputation (MI) algorithm.

The SPSS multiple imputation routine (MCMC algorithm known as Fully Conditional Specification) will be used to handle missing data.

Multiple imputation expectation-maximization algorithm [ 47] was used to estimate and replace missing observations when data loss on the DSS was minimal (i.e., 0.2%-2.3%).