crudeOR {BayesSenMC} | R Documentation |
Model without misclassification
Description
Generate a stanfit object corresponding to a posterior distribution of uncorrected odds ratio given no misclassification.
Usage
crudeOR(
a,
N1,
c,
N0,
logitpi0_prior = c(0, 10),
lor_prior = c(0, 2),
chains = 2,
traceplot = FALSE,
inc_warmup = FALSE,
window = NULL,
refresh = 0,
seed = 0,
...
)
Arguments
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. |
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. |
Value
It returns a stanfit object of this model, which inherits stanfit class methods. See rstan for more details.
Examples
# 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}
# 3 MCMC chains with 10000 iterations each
crudeOR(a = 66, N1 = 11782, c = 243, N0 = 57973, chains = 3, iter = 10000)