this is for holding javascript data
Anisha Keshavan edited In_a_multisite_model_we__.tex
over 8 years ago
Commit id: e59b4b5861c3903c601b8d7e7a340642552a2e65
deletions | additions
diff --git a/In_a_multisite_model_we__.tex b/In_a_multisite_model_we__.tex
index 3513996..7975c05 100644
--- a/In_a_multisite_model_we__.tex
+++ b/In_a_multisite_model_we__.tex
...
In a multisite model, we are sampling effect sizes from our set of sites, and then taking an average of those samples and testing whether or not this average effect is significantly different from 0. Becuase of this, its really important to have enough site-level samples to estimate a mean effect. The plots don't go down to the single site case because the power curves wouldn't apply there - the model would be different. In a single site case, one simply needs to power a standard T-test, given an effect size, number of subjects, false positive rate. If we take similar parameters to a single site case (effect size=0.2, alpha=0.002, power = 80\%), you would need 1400 subjects, all acquired at one site, to power this. The reason we don't do this is because it takes a really long time to acquire that many subjects for one site, and it is likely the scanner will go through upgrades or protocols will change in the meantime. The n cutoff
(#subjects (number subjects per site for our 20 sites) that we chose for this plot is 150 subjects per site, which we feel is the maximum amount we'd ask these sites to collect, though ideally this would be even lower, especially if researchers wanted to study very rare diseases.