Computes adjusted OR for given bias parameters
1 2 3 4 5 6 | prob_exposure_misc(ep_op, en_op, ep_on, en_on, n = 5000,
se_p_dist = list(func = runif, params = list(min = 0.8, max = 1)),
se_n_dist = list(func = runif, params = list(min = 0.8, max = 1)),
sp_p_dist = list(func = runif, params = list(min = 0.8, max = 1)),
sp_n_dist = list(func = runif, params = list(min = 0.8, max = 1)),
verbose = FALSE, nd_mc = TRUE)
|
ep_op |
Number of observations that were exposure positive and outcome positive |
en_op |
Number of observations that were exposure negative and outcome positive |
ep_on |
Number of observations that were exposure positive and outcome negative |
en_on |
Number of observations that were exposure negative and outcome negative |
n |
The number of simulations to perform |
se_p_dist |
Distribution of the sensitivity of exposure classification when the subject is outcome positive |
se_n_dist |
Distribution of the sensitivity of exposure classification when the subject is outcome negative |
sp_p_dist |
Distribution of the specificity of exposure classification when the subject is outcome positive |
sp_n_dist |
Distribution of the specificity of exposure classification when the subject is outcome negative |
verbose |
Should verbose results be produced? |
nd_mc |
Should the miss-classification be non-discriminative or not? |
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