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An odds ratio (OR) is a statistic that quantifies the strength of the association between two events, A and B. The odds ratio is defined as the ratio of the odds of event A taking place in the presence of B, and the odds of A in the absence of B. Due to symmetry, odds ratio reciprocally calculates the ratio of the odds of B occurring in the presence of A, and the odds of B in the absence of A.
In practice the odds ratio is commonly used for case-control studies, as the relative risk cannot be estimated. [1] In fact, the odds ratio has much more common use in statistics, since logistic regression, often associated with clinical trials, works with the log of the odds ratio, not relative risk. Because the (natural log of the) odds of a ...
Although in classical case–control studies, it remains true that the odds ratio can only approximate the relative risk in the case of rare diseases, there is a number of other types of studies (case–cohort, nested case–control, cohort studies) in which it was later shown that the odds ratio of exposure can be used to estimate the relative ...
While retrospective cohort studies try to compare the risk of developing a disease to some already known exposure factors, a case-control study will try to determine the possible exposure factors after a known disease incidence. Both the relative risk and odds ratio are relevant in retrospective cohort studies, but only the odds ratio can be ...
and = / / = While the prevalence is only 9% (9/100), the odds ratio (OR) is equal to 11.3 and the relative risk (RR) is equal to 7.2. Despite fulfilling the rare disease assumption overall, the OR and RR can hardly be considered to be approximately the same. However, the prevalence in the exposed group is 40%, which means is not sufficiently small
"OR" stands for "odds ratio" and "RR" stands for "relative risk". A prospective cohort study is a longitudinal cohort study that follows over time a group of similar individuals ( cohorts ) who differ with respect to certain factors under study to determine how these factors affect rates of a certain outcome . [ 1 ]
Frequently used measures of risk and benefit identified by Jerkel, Katz and Elmore, [4] describe measures of risk difference (attributable risk), rate difference (often expressed as the odds ratio or relative risk), population attributable risk (PAR), and the relative risk reduction, which can be recalculated into a measure of absolute benefit ...
Epidemiological (and other observational) studies typically highlight associations between exposures and outcomes, rather than causation. While some consider this a limitation of observational research, epidemiological models of causation (e.g. Bradford Hill criteria) [7] contend that an entire body of evidence is needed before determining if an association is truly causal. [8]