Panel bias is the difference between a statistic computed on a data vendor’s panel (cardholders, devices, users) and the same statistic on the population it stands for, caused by who is in the panel. Panel reweighting gives each panel member a weight so that the weighted panel matches known population totals; raking (iterative proportional fitting) does it with only the margins, adjusting the weights to each margin in turn until all match (Deming and Stephan, 1940).
ml_altdata.errors.