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Point prevalence is a measure of the proportion of people in a population who have a disease or condition at a particular time, such as a particular date. It is like ...
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.
Prevalence can also be measured with respect to a specific subgroup of a population. Incidence is usually more useful than prevalence in understanding the disease etiology: for example, if the incidence rate of a disease in a population increases, then there is a risk factor that promotes the incidence.
The Positive predictive value (PPV) of a test is the proportion of persons who are actually positive out of all those testing positive, and can be calculated from a sample as: PPV = True positive / Tested positive. If sensitivity, specificity, and prevalence are known, PPV can be calculated using Bayes' theorem.
In medical research, epidemiology, social science, and biology, a cross-sectional study (also known as a cross-sectional analysis, transverse study, prevalence study) is a type of observational study that analyzes data from a population, or a representative subset, at a specific point in time—that is, cross-sectional data. [definition needed]
Sensitivity and specificity are prevalence-independent test characteristics, as their values are intrinsic to the test and do not depend on the disease prevalence in the population of interest. [6] Positive and negative predictive values , but not sensitivity or specificity, are values influenced by the prevalence of disease in the population ...
A group of 58 researchers is calling for a new, better way to measure obesity. The global team’s recommendations were published in The Lancet Diabetes & Endocrinology on Jan. 14. Body mass index ...
Likelihood ratio is calculated from sensitivity and specificity of the test, and thereby it does not depend on prevalence in the reference group, [2] and, likewise, it does not change with changed pre-test probability, in contrast to positive or negative predictive values (which would change).