Research in the social sciences is routinely affected by missing data. Not addressing missing data appropriately may yield research findings that are either 'slightly off' or 'plain wrong'. This study demonstrates why and how frequently used simple remedies for missing data can impact on research results. The authors provide the target audience (i.e. producers and consumers of social science research) with a step-by-step guide on how to implement multiple imputation, which is the standard method for dealing with missing data. They encourage researchers to carefully consider the potential impact of incomplete information and to use modern missing data methods whenever possible in their own work.