 The paper discusses the importance of handling missing data appropriately in randomized clinical trials and presents various analytical approaches such as best worst and worst best sensitivity analyses, multiple imputation and full information maximum likelihood to minimize bias caused by unavoidable missing data. The authors also provide practical flowcharts on how to deal with missing data and an overview of the steps that always need to be considered during the analysis stage of a trial. This article was authored by Janus Christian Jakobsson, Christian Gludd, J.R.N. Wetherslev and others.