A selection modelling approach to analysing missing data of liver Cirrhosis patients
Methods for dealing with missing data in clinical trials have received increased attention from the regulators and practitioners in the pharmaceutical industry over the last few years. Consideration of missing data in a study is important as they can lead to substantial biases and have an impact on overall statistical power. This problem may be caused by patients dropping before completion of the study. The new guidelines of the International Conference on Harmonization place great emphasis on the...