Imputation performed multiple times on the same data.
1Missing data on effects and costs were imputed using multiple imputation techniques.
2For all outcomes, multiple imputation was used to account for missing data.
3We used multiple imputation with chained equations to estimate missing values.
4Missing data for plasma cholesterol and vitamin C were imputed using multiple imputation.
5For missing data, multiple imputation and responder analyses were performed.
6We used multiple imputation to correct estimates of prevalence and association for loss to follow-up.
7Results were robust to various sensitivity analyses such as competing risk analysis and multiple imputation.
8We used multiple imputation to account for missing data.
9Analyses were done by intention to treat, per protocol, and sensitivity analyses using multiple imputation.
10Further research is required into multiple imputation methods to address missing data issues in IV estimation.
11This study is a first step towards defining appropriate use of multiple imputation in longitudinal studies.
12Prevalence and correlates were estimated using multiple imputation.
13The base case analysis used an intention to treat approach on the imputed dataset using multiple imputation.
14We used intention-to-treat analysis, with multiple imputation for missing data, which was concealed to treatment group allocation.
15We used multiple imputation to impute missing confounder data for 29% of the study participants.
16We conclude that multiple imputation provides a practicable approach that can handle arbitrary patterns of systematic missingness.
Esta colocação é formada por:
Multiple imputation nas variantes da língua
Estados Unidos da América