Prepare Intercurrent Event Data — prepare_data

Builds a data_ice data.frame from a column in the dataset that flags intercurrent events. For each subject, the first visit (by factor level order) where the flag is TRUE is used as the ICE visit.

Usage

prepare_data_ice(data, vars, ice_col, strategy)

Arguments

data: A data.frame containing the analysis dataset.
vars: A vars object as created by rbmi::set_vars().
ice_col: Character string naming the column in data that indicates ICE occurrence. Accepted values are logical (TRUE/FALSE), character ("Y"/"N"), or numeric (1/0).
strategy: Character string specifying the imputation strategy to assign. Must be one of "MAR", "CR", "JR", "CIR", or "LMCF".

Value

A data.frame with columns corresponding to vars$subjid, vars$visit, and vars$strategy, suitable for passing to rbmi::draws().

Examples

library(rbmi)

dat <- data.frame(
  USUBJID = factor(rep(c("S1", "S2", "S3"), each = 3)),
  AVISIT = factor(rep(c("Week 4", "Week 8", "Week 12"), 3),
                  levels = c("Week 4", "Week 8", "Week 12")),
  TRT = factor(rep(c("Placebo", "Drug A", "Drug A"), each = 3)),
  CHG = rnorm(9),
  DISCFL = c("N","N","N", "N","Y","Y", "N","N","Y")
)

vars <- set_vars(
  subjid = "USUBJID",
  visit = "AVISIT",
  group = "TRT",
  outcome = "CHG"
)

ice <- prepare_data_ice(dat, vars, ice_col = "DISCFL", strategy = "JR")
print(ice)
#>   USUBJID  AVISIT strategy
#> 1      S2  Week 8       JR
#> 2      S3 Week 12       JR