Attrition often occurs in longitudinal studies, e.g., participants dropped out of the study, and results in missing data. There are three general categories of missing data mechanisms: missing completely at random (MCAR), missing at random (MAR), and not missing at random (MNAR). It is well known that if participants who returned to follow-up visits are systematically different from those who did not, using standard methods on only those who returned could provide biased results. Properly accounting for the missing data is critical to obtain valid results. Adjustment Cell Weighting (ACW) is one approach to adjust Baseline Sampling Weights (BSW) when missing is at random. This diversity supplement project proposes to implement ACW when analyzing complex longitudinal survey data using MLMs with 3 or more levels.