3 ms·
They do briefly mention "the relative cost of type I versus type II errors". Both errors (Type I - false positive, Type II - false negative) have some cost asso
by siginfo 9y ago
They do briefly mention "the relative cost of type I versus type II errors". Both errors (Type I - false positive, Type II - false negative) have some cost associated.
Money saved by using a small sample size is wasted trying to replicate a false positive result and by groups around the world that rely on that false result.
Requiring larger sample sizes would mean fewer experiments are carried out but we will have more confidence in the positive results produced. The outcome is fewer experiments wasted on following up on false positives. None of this requires a change in funding.
- rgejman 9y agoI really don't think the proposal to do "fewer, but better" experiments work with animal studies. They are so expensive and so complicated and so much work and only answer singular, small questions that you almost always need a ton of further follow up work. For instance, in the field I work in you have to spend days to months waiting for tumors to grow and then go and treat the animals every day for a couple of weeks with an IV drug (weekends too!). That is a a lot of work and at the end only tells you one piece of information about the drug: does it slow tumor growth in this one experimental model. It may in fact do that -- and you may get a really great p-value if you increase the number of mice -- but you still need to study the drug's pharmacokinetics, tissue distribution, in vivo mechanism of action (assuming you already know the in vitro mechanism of action). These are not just optional experiments that we require today to publish: this kind of work is essential to presenting a story about a new drug. It's not just about what it does, but how it works and universalizable it is.