Planned Missing Data Designs for Developmental Researchers
Abstract Planned missing data designs allow researchers to collect incomplete data from participants by randomly assigning participants to have missing items on a survey (multiform designs) or missing measurement occasions in a longitudinal design (wave missing designs) or by administering an intensive measure to a small subsample of a larger dataset (two-method measurement designs). When these designs are implemented correctly and when missingness is dealt with using a modern approach, the cost of data collection is lowered (sometimes dramatically) and reduced participant burden may result in higher validity as well as lower rates of unplanned missing data. In reviewing these planned missing designs, we briefly describe results of ongoing research on bias and power associated with each.