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For multiple imputation, this procedure is repeated m times.
While the general approach to deal with missing values is multiple imputation, this option is problematic in our case given that each individual has different bounds for the imputed value.
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The steps for multiple imputation involve: Imputation: This step involves the imputation of the missing values several times depending on the number of imputations stated.
Multiple imputation confirmed this association (adjusted OR = 1.52 (1.52-2.21.52
The robust estimations of multiple imputation in this simulation study are very satisfactory and promising.
Kaplan-Meier estimation was chosen for comparison with multiple imputation, because this method is often used to estimate cumulative success rates in IVF.
Finally, we investigated any influence missing data might have made using multiple imputation, and this had no overall impact on our results.
For the multiple imputation models, this statistic showed much more variation compared to the c statistic, as expected [ 59], but in all cases the statistic indicated acceptable model fit.
In a second step, missing data will be imputed using multiple imputation techniques; based on this imputed dataset, we will conduct a sensitivity analysis (all case analysis).
Nevertheless, the generally favourable performance of the SAS multiple imputation procedure in this analysis speaks to its general versatility and applicability in this context.
Following this, multiple imputation was used to impute all missing values for the EQ-5D and total cost estimates for non-responders to the 12-month questionnaire.
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