Often times you only see POA for clinical studies or studies involving humans. However, I'm under the impression that ANY scientist should perform POA before conducting and experiment to determine the correct sample size for an experiment. An underpowered study has the well known problem of having type II statistical errors, but I also found this interesting paper that say that paradoxically, if one finds a statistically significant finding in an underpowered study, it might actually be a type I error.


However, how do cell biologists conduct POA? The sample sizes needed that are mentioned in a POA are often huge (say 50-200 samples for an experiment designed for ANOVA w/ a power of 0.8 and moderate effect size if I'm using G*power correctly , sorry I'm a total noob when it comes to this). What am I doing wrong? Obviously it is impossible for a cell biologist to collect that many biologically independent samples, how do you calculate POA then? I know the "triplicate biological w/ triplicate technical" is quite standard in the literature, but what is so magical about 3x3? POA should be done to address proper sample size right? I'm just not sure how I go about doing it relative to cell biology work since it is virturally impossible to do studies with more than say 10 biologically independent samples/tests since the experiments would take forever. How do I determine proper sample size then? Just stick with 3 x 3 ?