Sample Size and Power: Fundamentals Part 1

good evening and welcome to tonight's lecture on sample size and power my name is dr laura lee johnson i'm an associate director at the united states food and drug administration so the disclaimer of course nothing that i say the fda wants to be construed as representing their views or policies so why do we care about sample size and

power let's think about this a little bit now last week you all heard a couple of lectures from paul joaquin this is actually a slide that he showed in another set of lectures that we gave and i think it's a very nice way to kind of set the mood for this lecture if you forget by the time we go through

all the formulas in the next 90 minutes power is basically the probability of getting a statistically significant result when in fact there's a clinically meaningful difference so this is kind of unknown to us right and part of what we're going to be discussing in that over the next several weeks is how do you know that

something's clinically meaningful but this in essence this idea of power we want to have high power right we want to have a high probability of seeing a statistically significant result in those hypotheses tests from last week if in fact there is this clinically meaningful difference so by definition those studies that have low power

are less likely to produce statistically significant results even when that clinically meaningful effect exists and that's the reason your animal care committees and the human subjects committees are going to say well is it ethical to do research if you don't have that much power so this becomes not just a i want to have

significant findings question it's also an ethical question is it worthwhile to put people at risk or their data or their privacy even at risk if you're not going to be able to tell that as one of my colleagues said there's a there there now the flip of this and how power and sample size and statistical significance