Data engineering and BI courses are free!
remiodCommon Parameters used by functions of remiod
object inheriting from class 'remoid'
the name of treatment variable. When necessary, its reference category,
i.e. control arm, can be set in refcats argument.
a method for obtaining multiple-imputed dataset. Options include
MAR, J2R, CR, and delta adjustment.
Default is MAR.
specific value used for Delta adjustment, applicable only for method="delta".
either algorithm tang_seq proposed by Tang (2018) or
jags the original method inherited in JAGS (Plummer 2003).
optional. manually specify an order for imputation models.
optional. specify whether ordinal variables should be treated as
categorical variables or continuous variables when they are
included as covariates in the sequential imputation models.
Default is TRUE, dummy variables will be created accordingly.
a small number used to adjusting Fish information matrix
scheme of distribution used for proposing coefficients of imputation models. scheme=1: beta ~ N( mean + inv(I)*score, inv(I)); scheme=2: beta ~ N( mean , inv(I)).
subset of parameters/variables/nodes (columns in the MCMC
sample). Follows the same principle as the argument
monitor_params and selected_parms.
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)
character string specifying the type of
progress bar. Possible values are "text" (default), "gui",
and "none" (see update). Note: when
sampling is performed in parallel it is not possible to
display a progress bar.
optional; seed value (for reproducibility)
logical, if TRUE, raw data will be included in imputed data sets with imputation ID = 0.
a list of arguments related to multiple imputation, including trtvar, algorithm, method, include, exclude_chains, thin, start, end, and seed.