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1. A repeated-measures test usually is more likely to detect a real treatment effect than an independent-measures test because the repeated-measures design typically has a smaller variance and a smaller estimated standard error.
2. A set of n = 16 difference scores has a mean of MD = 4 and a variance of s2 = 36. Cohen’s d for this sample is d = 4/6.
3. Repeated-measures designs are particularly well-suited to research studies examining learning or other changes that occur over time.
4. One advantage of a repeated-measures design is that it typically requires fewer participants than an independent-measures design.