A limitation of the above methods is that they do not model family structure or cryptic relatedness. These factors may lead to inflation in test statistics if not explicitly modeled, because samples that are correlated are assumed to be uncorrelated. Although correcting for genetic ancestry and then dividing by the residual λGC will restore an appropriate null distribution, association statistics that explicitly account for family structure or cryptic relatedness are likely to achieve higher power, due to improved weighting of the data.
