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In statistics and epidemiology, relative risk or risk ratio (RR) is the ratio of the probability of an event occurring (for example, developing a disease, being injured) in an exposed group to the probability of the event occurring in a comparison, non-exposed group. Relative risk includes two important features: (i) a comparison of risk between two "exposures" puts risks in context, and (ii) "exposure" is ensured by having proper denominators for each group representing the exposure : Consider an example where the probability of developing lung cancer among smokers was 20% and among non-smokers 1%. This situation is expressed in the 2 × 2 table to the right. Here, ''a'' = 20, ''b'' = 80, ''c'' = 1, and ''d'' = 99. Then the relative risk of cancer associated with smoking would be : Smokers would be twenty times as likely as non-smokers to develop lung cancer. The alternative term ''risk ratio'' is sometimes used because it is the ratio of the risk in the exposed divided by the risk in the unexposed. Relative risk contrasts with the actual or absolute risk, and may be confused with it in the media or elsewhere. ==Statistical use and meaning== Relative risk is used frequently in the statistical analysis of binary outcomes where the outcome of interest has relatively low probability. It is thus often suited to clinical trial data, where it is used to compare the risk of developing a disease, in people not receiving the new medical treatment (or receiving a placebo) versus people who are receiving an established (standard of care) treatment. Alternatively, it is used to compare the risk of developing a side effect in people receiving a drug as compared to the people who are not receiving the treatment (or receiving a placebo). It is particularly attractive because it can be calculated by hand in the simple case, but is also amenable to regression modelling, typically in a Poisson regression framework. In a simple comparison between an experimental group and a control group: *A relative risk of 1 means there is no difference in risk between the two groups. *An RR of < 1 means the event is less likely to occur in the experimental group than in the control group. *An RR of > 1 means the event is more likely to occur in the experimental group than in the control group. As a consequence of the Delta method, the log of the relative risk has a sampling distribution that is approximately normal with variance that can be estimated by a formula involving the number of subjects in each group and the event rates in each group (see Delta method).〔See e.g. Stata FAQ on CIs for odds ratios, hazard ratios, IRRs and RRRs at https://www.stata.com/support/faqs/stat/2deltameth.html〕 This permits the construction of a confidence interval (CI) which is symmetric around log(''RR''), i.e., : where is the standard score for the chosen level of significance and SE the standard error. The antilog can be taken of the two bounds of the log-CI, giving the high and low bounds for an asymmetric confidence interval around the relative risk. In regression models, the treatment is typically included as a dummy variable along with other factors that may affect risk. The relative risk is normally reported as calculated for the mean of the sample values of the explanatory variables. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「relative risk」の詳細全文を読む スポンサード リンク
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