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## Statistical Terms

*Aka: Statistical Terms, Statistical Significance, Statistically Significant, P-Value, Confidence Interval, Clinical Significance, Clinically Significant, Study Heterogeneity, Clinical Heterogeneity, Statistical Heterogeneity*

- See Also
- General
- Systems Evaluation
- Treatment Effect

- Epidemiology Rates
- Risks
- Decision Analysis (Decision Tree, Chance Graph)
- Screening Test
- Contingency Grid or Cross Tab (includes Statistics Example)
- Bayes Theorem (Bayesian Statistics)
- Fagan Nomogram
- Experimental Error (Experimental Bias)
- Lead-Time Bias
- Length Bias
- Selection Bias (Screening Bias)
- Likelihood Ratio (Positive Likelihood Ratio, Negative Likelihood Ratio)
- Number Needed to Screen (Number Needed to Treat, Absolute Risk Reduction, Relative Risk Reduction)
- Negative Predictive Value
- Positive Predictive Value
- Pre-Test Odds or Post-Test Odds
- Receiver Operating Characteristic
- Test Sensitivity (False Negative Rate)
- Test Specificity (False Positive Rate)
- U.S. Preventive Services Task Force Recommendations

- General
- Definition: Statistical Significance
- Statistical Significance is the probability that study findings are due to chance
- The risk of rejecting the null hypothesis when it is actually true
- In planning a study, a level of risk is chosen (e.g. 5% risk or P-Value of 0.05)

- P-Value is used to denote significance
- P-Value < 0.05: <5% that findings due to chance
- Reflects reproducibility of the study findings only
- Does not predict individual patient's effect

- Confidence Interval
- Provides a range of possible outcomes
- Example: Number Needed to Treat ranges from 20 to 100
- More clinically relevant

- Statistical Significance does not mean clinically useful
- See Clinical Significance below

- Statistical Significance is the probability that study findings are due to chance
- Definition: Clinical Significance
- Reflects how much of an effect a patient sees
- Example:
- Study shows drug x significantly improves Hair Growth
- Reality: Even the patient cannot see the difference

- Definition: Heterogeneity
- Step 1: Clinical Heterogeneity (study similarity)
- Assess similarity of who and what was evaluated across pooled, meta-analyzed studies
- Evaluates similarity between studies (systematic review, meta-analysis)
- Combined studies in meta-analysis should have similar protocols (e.g. inclusion and exclusion criteria)

- Step 2: Statistical Heterogeneity
- Assess similarity among study results (were they consistent)
- Assign a P-Value to a combined group of studies that reflects the difference in their results and the likelihood that this is due to random chance
- Large spread of data across more than one study (i.e. greater heterogeneity) suggests the studies should not be combined in meta-analysis

- References
- Newman in Majoewsky (2013) EM:Rap 13(7): 7

- Step 1: Clinical Heterogeneity (study similarity)