Maximizing Power in RCTs: Accounting for Outcome Saturation
Randomized Controlled Trials (RCTs) are the cornerstone of drug development. The conclusions drawn from these trials are often based on calculations of outcomes assessed with finite scales. However, their interpretation can be compromised when the outcome measurements reach the limit of these scales. This “floor effect” can lead to the saturation of the measured outcomes and an underestimation of the treatment effect of the study medication.
In this webinar, Arthur Ooghe, Data Mining & Statistical Research Specialist, will discuss the impact of this saturation effect on study power and how to account for it when designing an RCT. Arthur Ooghe will guide you through the calculations and results of how the effective power drops with increasing saturation rates. He will discuss possible methods to reduce this effect during the design of a study, and account for its impact on results.
Register here to take the first step toward improving the significance of your RCTs.
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