Extract a specified number of multiple imputed datasets

extract_MIdata(object, method = c("MAR", "J2R", "CR", "delta"), delta = 0,
  mi.setting = NULL, M = 10, minspace = 2, mess = FALSE)

Arguments

object: object inheriting from class 'remoid'
method: a method for obtaining multiple-imputed dataset. Options include MAR, J2R, CR, and delta adjustment. Default is MAR.
delta: specific value used for Delta adjustment, applicable only for method="delta".
mi.setting: a list of arguments related to multiple imputation, including trtvar, algorithm, method, include, exclude_chains, thin, start, end, and seed.
M: number of imputed datasets
minspace: minimum number of iterations between iterations to be chosen as imputed values (to prevent strong correlation between imputed datasets in the case of high autocorrelation of the MCMC chains).
mess: logical; should messages be given? Default is TRUE.

Value

A data.frame in which the imputed datasets are stacked onto each other. The variable Imp_ indexes the imputation, while .rownr links the rows to the rows of the original data. In cross-sectional datasets the variable .id is added as subject identifier.

Examples

# \donttest{
# data(schizow)

test = remiod(formula = y6 ~ tx + y0 + y1 + y3, data = schizow,
              trtvar = 'tx', algorithm = 'jags', method="MAR",
              ord_cov_dummy = FALSE, n.adapt = 10, n.chains = 1,
              n.iter = 100, thin = 2, warn = FALSE, seed = 1234)
#> NOTE: Stopping adaptation
#> 
#> 

extdt = extract_MIdata(object=test, method="J2R",mi.setting=NULL, M=10, minspace=2)

# }