Sentence examples for multiple imputation when from inspiring English sources

Missing values will be imputed using multiple imputation when meeting the assumption of missing (completely) at random, as imputation will increase precision and possibly reduce bias.

Using multiple imputation when adjusting for infant feeding did not change the risk estimate more than marginally (OR = 1.10; 95% CI = 0.64-1.89).

Missing data will be dealt with using multiple imputation when possible, specifically using the Multiple Imputation using Chained Equations (MICE) method.

It is hoped that the ideas presented in this paper can be further explored and developed so that, by addressing this practical dilemma, more medical researchers will be able to apply multiple imputation when data suffers from missingness.

Our aim was to compare three measures: the results of Pohar-Perme's net survival based on the database without causes of death the pooled cause-specific survival of Kaplan-Meier [ 18 ] after multiple imputation, when censoring other-cause deaths the pooled cause-specific cumulative incidence estimator after multiple imputation, accounting for deaths due to other causes as competing risks.

the results of Pohar-Perme's net survival based on the database without causes of death the pooled cause-specific survival of Kaplan-Meier [ 18] after multiple imputation, when censoring other-cause deaths the pooled cause-specific cumulative incidence estimator after multiple imputation, accounting for deaths due to other causes as competing risks.

Even if single imputation is a less proper procedure than multiple imputations when handling missing data, the differences between the methods would have been smaller if the same logistic regression model had been used for simulating the single imputations.

Given the increasing interest in multiple imputation methods, when several causes of death are observed and/or when a representative sample of causes of death is completed and validated by experts, we explored the interest of a multiple imputation approach to estimate cause-specific survival.

Missing or unknown data should therefore be accounted for (eg, by multiple imputation methods) when conducting stage-specific analyses in the DCR or other cancer registries.

To minimise the resulting loss of statistical power, multiple imputation was used when fitting models entering mutation status (Rubin, 1987).

The additional between-imputation uncertainty associated with multiple imputation is captured when applying bootstrapping techniques to generate cost utility planes and acceptability curves due to the use of all 25 000 replications (5000 from each imputed data set).