Authorea

Anisha Keshavan added I_see_that_needed_to__.tex over 8 years ago

Commit id: b337f018002eb0406b075661f619c193ff0f4a17

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I see that needed to emphasize that the number of phantom subjects do not contribute to the power equation in Figure 1. The power equation we derived does not account for any sort of calibration or scaling. Instead, it requires an estimate for $CV_a$, which is the variability of scaling biases between sites. Because we are not asking our consortium to change protocols, we knew that if we calculated this value from ADNI data (which has standardized acquisitions), our true variability would certainly be higher than that of ADNI, and sample sizes we would calculate would be smaller than we actually need. For other researchers planning multisite studies, they could use our measurements of $CV_a$ to get a better power estimate. So to power an estimate of $CV_a$, we'd need enough subjects to get accurate estimates, and enough sites to get a better variance estimate. This was restricted by funds. Ideally, we would have more than 12 subjects to get better estimates of scaling factor, and even get a better estimate of the intercept (This is listed as a study limitation in the discussion). We sampled from 20 sites because these same sites will be used in a future study on MS genetics and MRI phenotypes. In the text, I've emphasized that the derived power equation does not require phantom subjects or calibration to be used: "\textit{We emphasize that the use of phantom subjects do not directly contribute to the power equation in Figure 1, as it does not account for any sort of calibration or scaling. However, it requires an estimate for $CV_a$, which is the variability of scaling biases between sites. The goal of this study is to provide researchers with estimates of $CV_a$ from our set of calibration phantoms and our set of non-standardized MRI acquisitions. For a standardized set of scanners, these values may be considered an upper bound. }"