====== 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]]