Parameters used by several functions in JointAI
object inheriting from class 'JointAI'
optional; vector of names of variables for which no model should be specified. Note that this is only possible for completely observed variables and implies the assumptions of independence between the excluded variable and the incomplete variables.
name of the variable indicating the time of the measurement of a time-varying covariate in a proportional hazards survival model (also in a joint model). The variable specified in "timevar" will automatically be added to "no_model".
named vector specifying the type of the association used for a time-varying covariate in the linear predictor of the survival model when using a "JM" model. Implemented options are "underl.value" (linear predictor; default for covariates modelled using a Gaussian, Gamma, beta or log-normal distribution) covariates) and "obs.value" (the observed/imputed value; default for covariates modelled using other distributions).
subset of parameters/variables/nodes (columns in the MCMC
sample). Follows the same principle as the argument
monitor_params
in
*_imp
.
optional vector of the index numbers of chains that should be excluded
the first iteration of interest
(see window.mcmc
)
the last iteration of interest
(see window.mcmc
)
number of iterations for adaptation of the MCMC samplers
(see adapt
)
number of iterations of the MCMC chain (after adaptation;
see coda.samples
)
number of MCMC chains
logical; if TRUE
then messages generated by
rjags during compilation as well as the progress bar
for the adaptive phase will be suppressed,
(see jags.model
)
thinning interval (integer; see window.mcmc
).
For example, thin = 1
(default) will keep the MCMC samples
from all iterations; thin = 5
would only keep every 5th
iteration.
optional; number of rows in the plot layout; automatically chosen if unspecified
optional; number of columns in the plot layout; automatically chosen if unspecified
logical; Should ggplot be used instead of the base graphics?
logical; should warnings be given? Default is
TRUE
.
logical; should messages be given? Default is
TRUE
.
labels for the x- and y-axis
name of the column that specifies the multi-level grouping structure
logical; should the parameters of the main model be penalized
using ridge regression? Default is FALSE
optional; seed value (for reproducibility)
logical: should monitors for posterior predictive checks be set? (not yet used)