Friday, September 11, 2020 9:26:34 PM
Adjustment may need to occur to preserve the overall Type I error rate of the study
Every time the data is analysed, there’s a 5% chance of making a Type I error, if a=0.05. As the number of analyses increase, the chance of making a Type I error also increases. As a result, an alpha adjustment is often required.
Approaches for alpha adjustment
An alpha adjustment is needed to preserve the overall Type I error rate. Not surprisingly, researchers have established different methods to account for multiple analyses and ways to adjust the alpha. There isn’t any one consensus but there are a few that are commonly used.
Pocock o Same alpha for interim and final analysis o 2 analyses, a = 0.0294
Haybittle-Peto o Very strict alpha adjustment at interim, no adjustment at final o 2 analyses, a = 0.002 at interim and a = 0.05 at final
O’Brien-Fleming o Strict alpha adjustment at interim, small adjustment at final o 2 analyses, a = 0.0054 at interim and a = 0.0492 at final.
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This is a small Phase 2 trial they will use ( if stat sig ) to persuade the FDA to authorize widespread use of IV RLF-100 for hospitalized Covid patients .
They need this data to have the lowest P value possible .
Kiwi
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