What expresses the increase in primary outcome odds associated with a unit change in an input?

The odds ratio is a statistical measure that quantifies the relationship between an exposure and an outcome. It specifically illustrates how the odds of a primary outcome change with a unit change in an input variable. When the odds ratio is calculated, it provides insight into whether the occurrence of the outcome is more or less likely as the input changes, allowing researchers and analysts to understand the strength and direction of the relationship.

In contexts such as logistic regression, for instance, the odds ratio helps in interpreting the coefficients of the model, revealing how the likelihood of an event (the primary outcome) is affected by variations in predictors (input variables). A value greater than one indicates an increase in odds with increasing input, while a value less than one indicates a decrease.

The other options do not specifically describe the relationship between a change in input and changes in outcome odds in the clear, quantifiable way that the odds ratio does. While terms like probability estimate might refer to the likelihood of outcomes, they do not capture the multiplicative effect of a unit change in input on the odds of an event happening, which is central to understanding the function of odds ratios.