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Dealing with missing data: Key assumptions and methods …

Technical Report No. 4 May 6, 2013 Dealing with missing data : Key assumptions andmethods for applied analysisMarina paper was published in fulfillment of the requirements for PM931 Directed Study in Health Policy and Managementunder Professor Cindy Christiansen s direction. Michal Horn y, Jake Morgan, Kyung Min Lee, and Meng-YunLin provided helpful reviews and 1 Contents Executive Summary .. 2 Acronyms .. 3 1. Introduction .. 4 2. missing data mechanisms .. 5 3. Patterns of 6 4. methods for handling missing data .. 6 Conventional methods .. 6 Listwise deletion (or complete case analysis).

This tech report presents the basic concepts and methods used to deal with missing data. After explaining the missing data mechanisms and the patterns of missingness, the main conventional methodologies are reviewed, including Listwise deletion, Imputation methods, Multiple Imputation, Maximum Likelihood and Bayesian methods.

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  With, Data, Leading, Missing, Assumptions, Imputation, Missing data, Dealing with missing data, Key assumptions

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