RCT Biases

The plural form, encompassing the various systematic distortions that can arise in the design, conduct, analysis, and interpretation of randomized controlled trials. These include selection bias (even after randomization), attrition bias, detection bias, performance bias, publication bias (positive results favored), sponsorship bias, and the bias of unrealistic settings (artificiality bias). RCT Biases also cover cognitive biases among researchers who overconfidently interpret p‑values, ignore baseline imbalances, or dismiss null results as “failed trials.” Recognizing RCT Biases is essential for critical appraisal; it moves beyond the myth that RCTs are inherently objective and forces attention to the many ways even well‑randomized trials can mislead.

Example: “Her training in RCT Biases taught her to check not just randomization but also who dropped out, who measured outcomes, and who funded the study—because each can bias the result.”

RCT Biases by Abzugal Nammugal Enkigal April 21, 2026