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The risk difference (RD), excess risk, or attributable risk [1] is the difference between the risk of an outcome in the exposed group and the unexposed group. It is computed as I e − I u {\displaystyle I_{e}-I_{u}} , where I e {\displaystyle I_{e}} is the incidence in the exposed group, and I u {\displaystyle I_{u}} is the incidence in the ...
The relative risk (RR) or risk ratio is the ratio of the probability of an outcome in an exposed group to the probability of an outcome in an unexposed group. Together with risk difference and odds ratio, relative risk measures the association between the exposure and the outcome. [1]
Hazard ratios do not reflect a time unit of the study. The difference between hazard-based and time-based measures is akin to the difference between the odds of winning a race and the margin of victory. [3] When a study reports one hazard ratio per time period, it is assumed that difference between groups was proportional.
Similarly, attributable risk percent (ARP) is used as a synonym for the attributable risk percent among the exposed. [ 3 ] In climatology , fraction of attributable risk (FAR) is used to denote a proportion of adverse event risk attributable to the human influence on climate or other forcing factor.
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 ...
Attributable fraction for the population combines both the relative risk of an incident with respect to the factor, as well as the prevalence of the factor in the population. Values of AF p close to 1 indicate that both the relative risk is high, and that the risk factor is prevalent. In such case, removal of the risk factor will greatly reduce ...
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
It is defined as the inverse of the absolute risk increase, and computed as / (), where is the incidence in the treated (exposed) group, and is the incidence in the control (unexposed) group. [1] Intuitively, the lower the number needed to harm, the worse the risk factor, with 1 meaning that every exposed person is harmed.