Which advanced statistical technique adjusts for observable differences between patients in RWE analysis?

Answer

Propensity score matching

To address the inherent risk of confounding variables present in observational Real-World Data (RWD) analyses, researchers must employ sophisticated methodological tools. Propensity score matching is one such advanced statistical technique specifically designed for this purpose. It works by calculating a propensity score for each patient—the probability of receiving a particular intervention based on their observable characteristics. Researchers then use these scores to match treated patients with untreated patients who have similar underlying characteristics, thereby creating comparison groups that are balanced on known confounders, making the resulting Real-World Evidence (RWE) conclusions more scientifically sound.

Which advanced statistical technique adjusts for observable differences between patients in RWE analysis?

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