This workshop gives a broad, non-technical overview of modern techniques for dealing with missing data, focusing on multiple imputation (MI). Topics include the need for dealing with missing data, assumptions underlying MI, the logic of MI analysis, the advantages and disadvantages of different MI techniques, and best practices in analyzing MI data. Special attention will be given to the practical how-to of conducting MI analyses using R (a statistical program that is freely available), including data preparation, performing imputations, diagnosing problems, coding and working with MI data, and using MI data in analyses. Basic familiarity with R is required. Registration required; please click "more information" to access the registration form.