Final answer:
A major issue in repeated measures design is pseudoreplication, which results from a lack of true independence among the replicated measurements, undermining variance estimates and increasing the risk of Type II errors.
Step-by-step explanation:
One major issue with repeated measures design is pseudoreplication. This occurs when replicated measurements are not independent from each other, which can result from using the same experimental units over time or not considering the temporal relationship between samples. Without true independence among sampling units, statistical estimates of variance are compromised, leading to a higher chance of making Type II errors, which occurs when a study fails to detect a difference or effect that actually exists.
It should be noted that proper replication and the use of control groups are essential to avoid biased data and ensure that the results can be attributed to the experimental treatment. In the context of repeated measures designs, it's crucial to use statistical tests and experimental designs that account for potential temporal autocorrelation to mitigate the risk of pseudoreplication.