If sensitivity analysis shows changing results, what does that imply?

• A. Random variation
• B. Sufficient power
• C. Flawed assumptions
• D. Clear data

Answer: (C)

Sensitivity analysis asks how conclusions change when you adjust key inputs or assumptions. If the results shift when you tweak these assumptions, it means the study’s conclusions aren’t robust to those assumptions and may be driven by how things were assumed rather than by the data alone. This points to the possibility that the assumptions are flawed or at least uncertain, requiring closer scrutiny or alternative scenarios. It’s not about random variation from sampling (that would vary due to chance even with fixed assumptions), nor about having sufficient power (power affects the ability to detect an effect, not how sensitive results are to inputs), nor does it mean the data are clearly and unambiguously interpreted.