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Positive predictive value
12%
567/4853
Hawthorne effect
2%
103/4853
Effect size
3%
123/4853
Power
66%
3223/4853
P value
16%
797/4853
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The study power is defined as the ability of a study to detect the difference between two interventions if one in fact exists. The power of a statistical test is correlated to the magnitude of the treatment effect, the designated type I (alpha) and type II (beta) error rates, and the sample size n. The power is equal to (1-beta) whereby beta is the false negative rate. Kocher et al. present a Level 5 review of epidemiology and biostatistics. The review discusses study design, hypothesis testing, diagnostic performance, measures of effect, outcomes assessment, evidence-based medicine, and biostatistics. They discuss that in the orthopaedic literature power is typically set at 80%, (leaving a 20% chance that the study will display no significant association when there is an actual association.) Illustration A shows the interaction of study variables on the power of a study. Incorrect Answers: Answer 1: Positive predictive value is the probability that a patient with a positive test actually has the disease. This value is dependent on the prevalence of disease Answer 2: Hawthorne effect is a behavior that is changed when participants have knowledge that their behavior is being monitored. Answer 3: Effect size is the difference in outcome between the treatment group and the control group divided by the standard deviation. Answer 5: P value is defined as the probability, under the assumption of no difference (null hypothesis), of obtaining a result equal to or more extreme than what was actually observed if the experiment were repeated over and over
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