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RegisterHypotheses in non-inferiority trials [Power / Sample Size]
Hi Outlaw Torn
Let me cite Emmanuel Lesaffre:
"Demonstrating non-inferiority necessitates rejecting the null hypothesis (H0: ∆ > ∆NI) in favor of the alternative hypothesis (HA: ∆ < ∆NI) with an adapted classical statistical test (as for an equivalence test). A significant result (p < 0.025) means, in this case, that the experimental treatment is not (much) worse, i.e., non-inferior, to the control treatment, whereby the conclusion “non-inferior” depends on the chosen value for ∆NI."
I highly recommend you to read his great article (for me it's the best one). I think the relationships between equivalence, non-inferiority and superiority will be more clear.
❝ What I'm getting at is this. When conducting a non-inferiority trial, are the roles of the type-I and type-II error rate reversed since the null hypothesis and the alternative hypothesis are reversed (Null Hypothesis H0 states non non-inferiority (i.e. inferiority) while Alternative Hypothesis H1 states non-inferiority between Test and Reference products)?
Let me cite Emmanuel Lesaffre:
"Demonstrating non-inferiority necessitates rejecting the null hypothesis (H0: ∆ > ∆NI) in favor of the alternative hypothesis (HA: ∆ < ∆NI) with an adapted classical statistical test (as for an equivalence test). A significant result (p < 0.025) means, in this case, that the experimental treatment is not (much) worse, i.e., non-inferior, to the control treatment, whereby the conclusion “non-inferior” depends on the chosen value for ∆NI."
I highly recommend you to read his great article (for me it's the best one). I think the relationships between equivalence, non-inferiority and superiority will be more clear.
—
Kind regards,
Mittyri
Kind regards,
Mittyri
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