Repeated measures designs are generally considered to be more powerful because they require what?

Repeated measures designs are considered more powerful because they require smaller sample sizes compared to between-groups designs. This is largely attributed to the fact that each participant serves as their own control, which increases the precision of the measurements. By using the same participants across different conditions, variability due to individual differences is minimized, making it easier to detect significant effects with fewer participants.

The power of a statistical test is enhanced in repeated measures designs since the noise from individual differences is effectively accounted for, allowing researchers to identify the effects of the independent variable more reliably without needing a larger number of subjects. Consequently, these designs can yield more robust findings even when the sample size is limited, making them a favored choice in many experimental settings.