Sentence examples for multiple imputation software from inspiring English sources

We used multiple imputation software (Raghunathan et al. 2002) to impute missing data on family income and maternal education based on individual and census block group characteristics.

This method is widely used in multiple imputation software.

In order to include the participants who did not complete the presurvey in analyses of the outcome data and avoid the bias that often results from list-wise deletion, missing values were estimated using the multiple imputation software Amelia II (King, Honaker, Joseph, & Scheve, 2001).

In practice, implementations of multiple imputation in statistical software are made under the MAR assumption.

We used multiple imputation procedures [using IVEware software (University of Michigan, Ann Arbor, MI) with five imputations] to impute missing values in explanatory variables (Raghunathan et al. 2001).

To handle missing values in covariates (<20% missing), we performed multiple imputations with a software package by generating 5 independent datasets for all analyses.

Missing data were imputed with multiple imputation procedures using NORM, version 2, software (32).

Although a preliminary evaluation has been conducted using Bayesian multiple imputation in the empirical software engineering domain, this is the first work to provide a thorough and detailed analysis of this technique.

With the development of readily available and easily implemented software, multiple imputation methods for dealing with missing data are becoming more popular in epidemiological studies that have incomplete measured variables.

Missing data was handled using multiple imputation with imputed data generated using a sequential regression imputation method via the software package IVEware [ 31].

To validate our encoding strategy (ie, when an item was not recorded as abnormal, it was considered normal), we compared our results obtained for the association between neurological status at term and outcome at 2 years, with the results obtained with 50 datasets where non-recorded items were imputed using a multiple imputation module included in the SPSS Statistics software.