SENSITIVITY ANALYSIS OF MISSING DATA: MILK PROTEIN EXAMPLE

Abstract

Missing data are one of the most serious problems that should be solved in the statistical analysis of biological experiments. In this report different techniques for handling missing information are shown using an example. It is also shown how sensitive the conclusions of the study can be with respect to the way the missing data are analised. The missing data process is studied in the framework of longitudinal data.