I'm asking myself the question of why studies with small sample sizes are not as convincing as those with larger sample sizes, and when this becomes a statistical issue. A complaint I've heard a lot with studies is while they show a certain "desired" result (e.g. the treatment group had lower cholesterol than the placebo group), the sample size was small.
Statistically, if you have the sample size to detect an effect, then the sample size was large enough in that sense. So at that point, on what grounds could you claim a higher sample size would be better? To get more exact confidence intervals if they are asymptotic?
Personally I would feel more convinced with a sample of 1000 rather than 500, but I can't identify technically where this makes a difference aside from precision.