imImpAll_mice: Impute missing data by mice

In idem: Inference in Randomized Controlled Trials with Death and Missingness

Impute missing data by mice

Description

Conduct imputation using the NARFCS model implemented in the mice package

Usage

imImpAll_mice(
  im.data,
  deltas = 0,
  n.imp = 5,
  endponly = TRUE,
  seed = NULL,
  ...
)

Arguments

im.data	A class IDEMDATA object generated by imData
deltas	Vector of imputation sensitivity parameters
n.imp	Number of complete datasets required
endponly	Logical variable that indicates whether clinical outcomes not used in calculating the functional outcome are considered as missing and should be imputed. The default is FALSE, indicating that all missing clinical outcomes will be imputed sequentially
seed	Random seed
...	Parameters for mice

Value

A class IDEMIMP list with components

lst.var

List of parameters

complete

A dataset with the original data for the subset of subjects who died at the end of the study or had no missing outcomes and the n.imp imputed missing outcomes for subjects who need missing value imputation.

n.imp

Number of imputed complete datasets

deltas

Imputation sensitivity parameters

org.data

Original dataset

Examples

## Not run: 
rst.abc <- imData(abc, trt="TRT", surv="SURV", outcome=c("Y1","Y2"),
                 y0=NULL, endfml="Y2",
                 trt.label = c("UC+SBT", "SAT+SBT"),
                 cov=c("AGE"), duration=365, bounds=c(0,100));
rst.imp <- imImpAll_mice(rst.abc, deltas=c(-0.25,0,0.25));
## End(Not run)

idem documentation built on Aug. 9, 2023, 5:08 p.m.