| posttest_series {covidprobability} | R Documentation |
Calculate post-test probability if testing occurred on each day in a series
Description
Given an initial pretest probability, and assuming symptoms never arise, with each passing day the pretest probability will be lower, given the person did not experience symptoms. This returns a vector of posttest probabilities which takes all of the above into account, assuming a negative test on each day. Note this is not a time series, and does not reflect if serial testing were done each day and assumes testing was only done once.
Usage
posttest_series(pre0, asympt, days = 14, mu = 1.63, sigma = 0.5, sens, spec)
Arguments
pre0 |
The pretest probability on day 0 (at exposure) |
asympt |
The proportion of infected patients expected to remain asymptomatic throughout the course of infection |
days |
Days since exposure for calculation range |
mu |
The mean of a lognormal distribution that approximates the incubation period for COVID-19. E.g. 1.63 (see reference). |
sigma |
The standard deviation of a lognormal distribution that approximates the incubation period for COVID-19. E.g. 0.5 (see reference). |
sens |
A vector of sensitivities by day since exposure |
spec |
The test specificity |
Value
A vector of posttest probabilities