Correctly specifying the imputation model when conducting multiple imputation remains one of the most significant challenges in missing data analysis. This dissertation introduces a robust multiple imputation technique, Multiple Imputation with the Bayesian Elastic Net (MIBEN), as a remedy for this difficulty. A Monte Carlo simulation study was conducted to assess the performance of the MIBEN technique and compare it to several state-of-the-art multiple imputation methods.
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