If there are no major differences, it may be more reasonable to assume that mortality was happening across the entire sample and is not biasing results greatly. But if the pretest differences are large, one must be concerned about the potential biasing effects of mortality. OK, I know that's gibberish. Let me try again. Furthermore, assume that your sample consists of low pretest scorers.
Regression is a confusing threat to understand at first.
Most of them would score low on the posttest, but they aren't likely to be the lowest ten percent twice. For instance, maybe there were a few kids on the pretest who got lucky on a few guesses and scored at the eleventh percentile who won't get so lucky next time. This purely statistical phenomenon is what we mean by a regression threat. To see a more detailed discussion of why regression threats occur and how to estimate them, click here . While there are several ways to rule out threats, one of the most common approaches to ruling out the ones listed above is through your research design.