Generate a missingness mask — missingness

Draws, for every row of data and every variable in specification, whether that cell is missing, by comparing a uniform draw against the row's probability. The mask is returned rather than applied, so the complete data and the mask that hides part of it can both be kept; observed_data() joins them.

Usage

missingness_matrix(
  data,
  specification,
  id = NULL,
  period = NULL,
  seed = NULL,
  envir = parent.frame()
)

Arguments

data: Complete base data.frame, or a simulab_sim, with at least one row. Every target variable of specification must be one of its columns.
specification: Definitions from define_missingnesses(), a simulab_missing_spec object.
id: Optional unit identifier. A single string naming a column of data, or NULL (the default). It is required by the baseline and monotone rules and is carried into the mask.
period: Optional period variable that orders a unit's rows. A single string naming a column of data, or NULL (the default). It is required by the baseline and monotone rules and is carried into the mask.
seed: Optional random seed. A single number, or NULL (the default).
envir: Environment the formulas are evaluated in after the data columns. Defaults to the caller's environment.

Value

A base data.frame with one row per row of data, holding the id and period columns when they are given, or a single row column numbering the rows when neither is, followed by one logical column per target variable of specification, named after that variable. Variables of data that specification says nothing about get no column.

Examples

data <- data.frame(id = 1:100, baseline = stats::rnorm(100), outcome = stats::rnorm(100))
specification <- define_missingnesses(
  define_missingness("outcome", formula = "0.2")
)

mask <- missingness_matrix(data, specification = specification, seed = 1)
head(mask)
#>   row outcome
#> 1   1   FALSE
#> 2   2   FALSE
#> 3   3   FALSE
#> 4   4   FALSE
#> 5   5   FALSE
#> 6   6   FALSE