The study looked at how missing data in scientific trials can affect the accuracy of estimates. They found that bias in the estimates was mainly due to the method used, not the missing data itself. The bias increased when the ratio of genotype variance to error variance was small. The type of missing data pattern (random or not) didn't make a big difference in the bias. So, the researchers concluded that selection doesn't make the estimates more biased.