Odds ratio
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The odds ratio is a measure of effect size particularly important in Bayesian statistics and logistic regression.
It is defined as the ratio of the odds of an event occurring in one group to the odds of it occurring in another group, or to a sample-based estimate of that ratio. These groups might be men and women, an experimental group and a control group, or any other dichotomous classification. If the probabilities of the event in each of the groups are p (first group) and q (second group), then the odds ratio is:
- [=\frac.]
For example, suppose that in a sample of 100 men, 90 have drunk beer in the previous week, while in a sample of 100 women only 20 have drunk beer in the same period. The odds of a man drinking beer are 90 to 10, or 9:1, while the odds of a woman drinking beer are only 20 to 80, or 1:4 = 0.25:1. Now, 9/0.25 = 36, so the odds ratio is 36, showing that men are much more likely to drink beer than women. Using the above formula for the calculation yields:
- [=\frac = = 36.]
Taking the logarithm of the odds ratio ameliorates this effect, and also improves symmetry. For example, using natural logarithms, an odds ratio of 36 maps to 3.584, an odds ratio of one maps to zero, and an odds ratio of 1/36 maps to -3.584.
The logarithm of the odds-ratio is the difference of the logits of the probabilities.
The increased use of logistic regression in medical and social science research means that the odds ratio is commonly used as a means of expressing the results in some forms of clinical trials, such as case-controlled trials, and in survey research. It is often abbreviated "OR" in reports. When data from multiple surveys is combined, it will often be expressed as "Pooled OR".
See also
External links
- [The Odds Ratio Generator - Freeware]
- [Odds Ratio Calculator - website]
- [Odds ratio definition and examples]
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