Show pageBacklinksCite current pageExport to PDFBack to top This page is read only. You can view the source, but not change it. Ask your administrator if you think this is wrong. ====== Overestimation ====== **Overestimation** refers to the act of assigning **greater value, effect, importance, or certainty** to a finding or intervention than is justified by the available evidence. ===== Characteristics ===== * Reporting results with **exaggerated effect sizes** * Presenting **statistically significant** but **clinically trivial** findings as meaningful * Ignoring **confidence intervals**, **sample limitations**, or **study design flaws** * Assuming an intervention is more effective than it truly is due to bias or methodological error ===== Common Causes ===== * **Small sample sizes** (→ inflated effect estimates) * **Selective reporting** or **publication bias** * **Lack of blinding** or **randomization** * **Inappropriate statistical methods** (e.g., p-hacking) ===== Examples in Medical Research ===== * A pilot study claims "dramatic symptom reduction" based on a 10-patient sample * Overinterpreting early subgroup analyses or interim data * Drawing strong conclusions from observational associations without controlling for confounders ===== Why It Matters ===== * Leads to **misinformed clinical decisions** * May result in **harmful overuse** of unproven treatments * Fuels **false expectations** among clinicians, patients, and policymakers ===== Related Terms ===== * [[effect_size|Effect Size]] * [[sample_size_fallacy|Sample Size Fallacy]] * [[rhetorical_inflation|Rhetorical Inflation]] * [[spin|Scientific Spin]] * [[overgeneralization|Overgeneralization]] ===== See Also ===== * [[critical_review|Critical Reading in Medical Literature]] * [[clinical_significance|Statistical vs. Clinical Significance]] overestimation.txt Last modified: 2025/06/15 10:34by administrador