A planned missingness data study design takes advantage of modern techniques for handling data missingness that is MCAR (Missing Completely at Random) and MAR (Missing at Random) (Brown, 2006; Enders, 2010). As modern data imputation techniques have improved, this study design option has become a powerful, cost-effective option for collecting the most data across the largest sample possible, while keeping the fatigue effect and expense of the study minimized (Little, 2010a, 2010b, 2012). The purpose of this guide is to provide an applied example for designing the surveys necessary when conducting a planned missingness research study design