Year: 2015
Type: dissertation
Abstract: 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.
Author: Kyle M. Lang
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2187741742