Missing Data Methodology

Evaluation and Development of Approaches for Handling Missing Data in Complex Longitudinal Studies

Handling missing data is an important process in the analysis of health research studies. For complex study designs, information on how the study was conducted needs to be incorporated into the process and it is currently unclear how best to do this. My project aims to evaluate and compare the various methods available, and produce guidance on the issue for use in the analysis of public health studies.