Search results
Results from the WOW.Com Content Network
In Bayesian statistics, the posterior predictive distribution is the distribution of possible unobserved values conditional on the observed values. [1] [2]Given a set of N i.i.d. observations = {, …,}, a new value ~ will be drawn from a distribution that depends on a parameter , where is the parameter space.
The results of this test must be interpreted carefully. The person's medical risk factors determine at which increment (5 mm, 10 mm, or 15 mm) of induration the result is considered positive. [12] A positive result indicates TB exposure. 5 mm or more is positive in An HIV-positive person; Persons with recent contacts with a TB patient
Posterior probability is a conditional probability conditioned on randomly observed data. Hence it is a random variable. For a random variable, it is important to summarize its amount of uncertainty. One way to achieve this goal is to provide a credible interval of the posterior probability. [11]
Predictive power is a Bayesian power. A parameter in Bayesian setting is a random variable. Predictive power is a function of a parameter(s), therefore predictive power is also a variable. Both conditional power and predictive power use statistical significance as success criteria. However statistical significance is often not enough to define ...
In clinical practice, post-test probabilities are often just estimated or even guessed. This is usually acceptable in the finding of a pathognomonic sign or symptom, in which case it is almost certain that the target condition is present; or in the absence of finding a sine qua non sign or symptom, in which case it is almost certain that the target condition is absent.
The positive predictive value and negative predictive value of all tests, including HIV tests, take into account the prior probability of having a disease along with the accuracy of the testing method to determine a new degree of belief that an individual has or does not have a disease (also known as the posterior probability). The chance that ...
[7] [8] If a minor reaction is considered doubtful, the OT test is less accurate and may fail to detect TB, producing a false negative. [2] If all doubtful indications are instead classified as positive, there is no significant difference between the OT test, the PPD tine test, or the Mantoux test. [3]
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.