Missing Data and How to Deal With It
Leader: Isaac Washburn
About the Session
What is your sentence that you copy and paste in journal articles for how you handle missing data? It is time to learn this for yourself. This hands-on workshop will introduce researchers to the nature of missing data and how it biases our analyses. Solutions to missing data (with examples in Stata, SPSS, and Mplus) will then be presented. These solutions will include Full-information Maximum Likelihood and Multiple Imputation. Finally, some benefits of missing data will be discussed (i.e. missing by design studies).