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**Sensitivity & Specificity**

Sensitivity – Likeliness of resulting in a true positive

Specificity – Likeliness of resulting in a true negative

(Boswell, C., & Cannon, S., 2017)

**Reliability** – the amount of dependability for consistent results (Boswell, C., & Cannon, S., 2017). For example, are the results of a tape measure for waist circumference dependable if I measure a person week after week? If my procedure is exactly the same, then yes. A tape measure provides high reliability if it is used within a standardized procedure.

**Measures of effect** include odds ratio, risk difference, relative risk, confidence interval, and number needed to treat. These are measurements that compare between groups the rate of disease manifestation (Tripepi et al., 2007).

**Odds ratio** asks “what are the odds?” What is the likeliness of a specific disease incidence in the groups of comparison? If I smoke cigarettes habitually, what is the probability I will get COPD – a question an odds ratio can address. An odds ratio of 1.91 would mean 91% probable (Tripepi et al., 2007).

**Confidence Interval** is a common measure of effect in statistical analysis. It is a descriptor of the risk ratio, the likeliness of a specific incidence of occurring. The CI is the probability of the incidence will likely occur. >95% CI is ideal for statistical relevance (Tripepi et al., 2007).

**References**

Boswell, C., & Cannon, S. (2017). *Introduction to nursing research: Incorporating evidence-*

* based practice *(4th ed.). Burlington, MA: Jones & Bartlett Learning. pp. 340-342

Tripepi, G., Jager, K. J., Dekker, F. W., Wanner, C., & Zoccali, C. (2007). Measures of effect:

Relative risks, odds ratios, risk difference, and ‘number needed to treat.’ Kidney

International, 72(7), 789–791. https://doi.org/10.1038/sj.ki.5002432

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