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Reliability, Odds ratio, Confidence interval, and more

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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).


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.


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