Description Usage Arguments Details Examples
View source: R/posttest_probs.R
##TODO: check maths
1 | posttest_pos_aggregate(n_pos, n_neg, sens, spec, prev)
|
n_pos |
Number of positives |
n_neg |
Number of negatives |
sens |
Sensitivity |
spec |
Specificity |
prev |
Prevalence |
See Modeling in Medical Decision Making: A Bayesian Approach Giovanni Parmigiani book example
Currently, only computes with pmf for prevalence of two probabilities i.e. p(x=1)=prevalence so then the likelihood reeduces to sensitivity and specificity if using a distn for prevalence eg beta/uniform then will need to integrate denominator.
1 | posttest_pos_aggregate(n_pos = 10, n_neg = 10, sens = 0.9, spec = 0.9, prev = 0.1)
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