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The positive predictive value (PPV), or precision, is defined as = + = where a "true positive" is the event that the test makes a positive prediction, and the subject has a positive result under the gold standard, and a "false positive" is the event that the test makes a positive prediction, and the subject has a negative result under the gold standard.
Also, there are risk assessment tools for estimating the combined risk of several risk factors, such as the online tool from the Framingham Heart Study for estimating the risk for coronary heart disease outcomes using multiple risk factors, including age, gender, blood lipids, blood pressure and smoking, being much more accurate than ...
Specific to public health policy, a determinant is a health risk that is general, abstract, related to inequalities, and difficult for an individual to control. [2] [3] [4] For example, poverty is known to be a determinant of an individual's standard of health. Risk factors may be used to identify high-risk people.
The false positive rate (FPR) is the proportion of all negatives that still yield positive test outcomes, i.e., the conditional probability of a positive test result given an event that was not present. The false positive rate is equal to the significance level. The specificity of the test is equal to 1 minus the false positive rate.
Here "T+" or "T−" denote that the result of the test is positive or negative, respectively. Likewise, "D+" or "D−" denote that the disease is present or absent, respectively. So "true positives" are those that test positive (T+) and have the disease (D+), and "false positives" are those that test positive (T+) but do not have the disease (D ...
RR < 1 means that the risk of the outcome is decreased by the exposure, which is a "protective factor" RR > 1 means that the risk of the outcome is increased by the exposure, which is a "risk factor" As always, correlation does not mean causation; the causation could be reversed, or they could both be caused by a common confounding variable ...
Risk is the lack of certainty about the outcome of making a particular choice. Statistically, the level of downside risk can be calculated as the product of the probability that harm occurs (e.g., that an accident happens) multiplied by the severity of that harm (i.e., the average amount of harm or more conservatively the maximum credible amount of harm).
It assigns scores to individuals based on risk factors; a higher score reflects higher risk. The score reflects the level of risk in the presence of some risk factors (e.g. risk of mortality or disease in the presence of symptoms or genetic profile, risk financial loss considering credit and financial history, etc.).