correctedOR {BayesSenMC} | R Documentation |
Generate a stanfit object corresponding to a posterior distribution of corrected odds ratio given nondifferential misclassification with Se and Sp (i.e., both are constant and at least one of Se or Sp is lower than 1).
correctedOR(
a,
N1,
c,
N0,
prior_list = NULL,
se = NULL,
sp = NULL,
logitpi0_prior = c(0, 10),
lor_prior = c(0, 2),
chains = 2,
traceplot = FALSE,
inc_warmup = FALSE,
window = NULL,
refresh = 0,
seed = 0,
...
)
a |
number of exposed subjects in the case group. |
N1 |
number of total subjects in the case group. |
c |
number of exposed subjects in the control group. |
N0 |
number of total subjects in the control group. |
prior_list |
list of priors. Can be replaced by the function call to |
se |
sensitivity. Do not have to specify this if |
sp |
specificity. Do not have to specify this if |
logitpi0_prior |
mean and sd of the prior normal distribution of |
lor_prior |
mean and sd of the prior normal distribution of corrected log odds ratio. Default to |
chains |
number of Markov Chains. Default to 2. |
traceplot |
Logical, defaulting to |
inc_warmup |
Only evaluated when |
window |
Only evaluated when |
refresh |
an integer value used to control how often the progress of sampling is reported. By default, the progress indicator is turned off, thus refresh <= 0. If on, refresh = max(iter/10, 1) is generally recommended. |
seed |
the seed for random number generation. Default to 0. See stan for more details. |
... |
optional parameters passed to stan. |
It returns a stanfit object of this model, which inherits stanfit class methods. See rstan for more details.
# Case-control study data of Bipolar Disorder with rheumatoid arthritis (Farhi et al. 2016)
# Data from \url{https://www.sciencedirect.com/science/article/pii/S0165032715303864#bib13}\
mod <- nlmeNDiff(bd_meta, lower = 0) # see \code{nlmeNDiff()} for detailed example.
prior_list <- paramEst(mod)
correctedOR(a = 66, N1 = 11782, c = 243, N0 = 57973, prior_list = prior_list,
chains = 3, iter = 10000)