Techniques for analyzing incomplete data in public health research

Abstract

Statistical inference of incomplete data has been an obstacle in numerous areas of research, and public health studies are no exception. Since studies in this field are often survey-based and can center around sensitive personal information, it can make them susceptible to missing records. This chapter discusses the causes and problems created by incomplete data and recommends techniques for how to handle it through multiple imputation.