Hi all,
I have a question I haven't been able to answer. I hope you can help me
.
I use G power to estimate sample size. In my case, the estimated sample size for my desired effect size = 0.25 and power = 0,95, is 400. But the estimated sample size for an effect size = 0.5 and power = 0,95, is 107!
As far as I understand, larger effect sizes and greater power are indicators of better statistical estimates (or reduce the probability of type-I and type-II errors). Also, the larger the sample, the more accurate to the "reality". Therefore, why do I need fewer subjects when I aim for more strict parameters?
Thanks!
I have a question I haven't been able to answer. I hope you can help me
I use G power to estimate sample size. In my case, the estimated sample size for my desired effect size = 0.25 and power = 0,95, is 400. But the estimated sample size for an effect size = 0.5 and power = 0,95, is 107!
As far as I understand, larger effect sizes and greater power are indicators of better statistical estimates (or reduce the probability of type-I and type-II errors). Also, the larger the sample, the more accurate to the "reality". Therefore, why do I need fewer subjects when I aim for more strict parameters?
Thanks!