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We used the multiple imputation by chained equation procedure to address the issue of missing cost and EQ-5D data.
Our base case analysis included 135 women based on recommendations for multiple imputation of missing cost and HSUV data [ 35].
For the CUA and CEA, missing cost and effect data will be imputed using multiple imputation [ 52].
We will follow recommendations by the International Society for Pharmacoeconomics and Outcomes Research for missing cost and effectiveness data.
Multiple imputation according to the MICE algorithm will be used to impute missing cost and effect data [ 44].
For the economic evaluation, missing cost and effect data will be imputed using multiple imputation according to the Multivariate Imputation by Chained Equations (MICE) algorithm developed by van Buuren using predictive mean matching and fully conditional specification [ 55].
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Missing costs and QALY data were imputed using a regression-based method adjusting for baseline variables costs, EQ-5D-3L scores, GHQ-12 score, and the type of MS. Non-parametric bootstrapping methods were used to account for non-normality in the distribution of cost data [27].
Missing cost- and effect data are imputed using multiple imputation according to the MICE algorithm developed by van Buuren [ 64].
The questionnaire consists of 11 questions and provides information about labor (missing) costs and additional paid working hours.
We will use propensity scores, stratified by treatment group, for imputing missing costs and effectiveness data due to attrition.
To account for missing costs and health outcomes due to incomplete projects and the uncertainty so introduced, we will perform sensitivity analyses using various imputation techniques.
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