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Change in the probability of testing fevers was not well described by the logistic regression; testing rates fluctuated over time and were determined by many factors.
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We are also interested in the extent to which availability of HIVST would, by providing a convenient and confidential option, increase the probability of testing in people who are not resistant to HTC but have never been tested before; similarly, we are interested in the frequency of repeat HIVST.
The probability of testing positive in the iELISA was affected by age-by-sex interaction, sampling month, and the number of open-air bred pigs per square Km in the sampling municipality.
Again the consequence of removing the actives from the Prior was a threefold reduction in the probability of generating a test set active: the difference between the two Priors is directly mirrored by their corresponding Agents.
In other words, the probability of a test giving a positive result is not only dependent on the sensitivity of the test but depends also on the quantity of bacteria present in the sputum and hence on the condition of the specific patient.
In this context, the probability of a test yielding a positive diagnosis is simply the fraction of the undiagnosed population that is HIV positive.
In the model, the probability of a test being positive is the naive compartmental model probability, given by the HIV prevalence in the undiagnosed segment of the subpopulation, times the modifying factor.
These test results would lead to a clinically meaningful increase in the probability of RIF-resistance from 5%to83%3% if a test is positive, while a negative test would virtually rule out RIF-resistance.
There was no difference between the groups in the probability of being treated given a positive test (RR 0.95, 95% CI 0.86-1.1).
These numbers of unsuccessful attempts were used to test for differences in the probability of mating success (see below).
The likelihood ratio (LR) is the ratio of two probabilities, namely the probability that a specific test result is obtained in patients with the disease divided by the probability of a test result in patients without the disease.
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