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What is an odds ratio? An odds ratio (OR) is a measure of association between an exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure.
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- Odds Ratio - StatPearls - NCBI Bookshelf
The odds ratio (OR) is a measure of how strongly an event is...
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May 22, 2023 · The odds ratio (OR) is a measure of how strongly an event is associated with exposure. The odds ratio is a ratio of two sets of odds: the odds of the event occurring in an exposed group versus the odds of the event occurring in a non-exposed group.
- Steven Tenny, Mary R. Hoffman
- 2023/05/22
- University of Nebraska Medical Center
- What Is An Odds Ratio?
- What Are Odds in Statistics?
- Odds Ratios Interpretation For Two Conditions
- How to Interpret Odds Ratios
- How to Calculate An Odds Ratio
- Odds Ratios For Continuous Variables
- Interpreting Confidence Intervals and P-Values For Odds Ratios
An odds ratio (OR) calculates the relationship between a variable and the likelihood of an event occurring. A common interpretation for odds ratios is identifying risk factorsby assessing the relationship between exposure to a risk factor and a medical outcome. For example, is there an association between exposure to a chemical and a disease? To ca...
Before you can calculate and interpret an odds ratio, you must know what the odds of an event represents. In common usage, people tend to use odds and probability interchangeably. However, in statistics, it has an exact definition. It is a specific type of probability. Odds relate to a binary outcome where the outcome either occurs or does not occu...
Odds ratios with groups quantify the strength of the relationship between two conditions. They indicate how likely an outcome is to occur in one context relative to another. The odds ratio formula below shows how to calculate it for conditions A and B. The denominator (condition B) in the odds ratio formula is the baseline or control group. Consequ...
Due to the odds ratio formula, the value of one becomes critical during interpretation because it indicates both conditions have equal odds. Consequently, analysts always compare their OR results to one when interpreting the results. As the OR moves away from one in either direction, the association between the condition and outcome becomes stronge...
The equation below expands the earlier odds ratio formula for calculating an OR with two conditions (A and B). Again, it’s the ratio of two odds. Hence, the numerator and denominator are also ratios. In the infection example above, we assessed the relationship between treatment and the odds of being infected. Our two conditions were the treatment (...
When you perform binary logistic regression using the logit transformation, you can obtain ORs for continuous variables. Those odds ratio formulas and calculations are more complex and go beyond the scope of this post. However, I will show you how to interpret odds ratios for continuous variables. Unlike the groups in the previous examples, a conti...
So far, we’ve only looked at the point estimates for odds ratios. Those are the sample estimates that are a single value. However, sample estimates always have a margin of error thanks to sampling error. Confidence intervals and hypothesis tests (p-values) can account for that margin of error when you’re using samples to draw conclusions about popu...
Odds ratio. An odds ratio (OR) is another measure of association that quantifies the relationship between an exposure with two categories and health outcome. Referring to the four cells in Table 3.15, the odds ratio is calculated as
The odds ratio is used when one of two possible events or outcomes are measured, and there is a supposed causative factor. The odds ratio is a versatile and robust statistic. For example, it can calculate the odds of an event happening given a particular treatment intervention (1).
- Mary L. McHugh
- 2009
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.
The estimated odds ratio is 1.4 when simultaneously accounting for specialty, spending region, sole proprietor status, sex, and the interaction between specialty and sex. A different odds ratio would be found if the model included a different set of explanatory variables.