Define missingness for one variable

Records the rule that decides whether one variable is missing for a row. The rule is a formula evaluated row by row against the data, so missingness may depend on any column: on a fully observed covariate, which is MAR, or on the variable's own value, which is MNAR.

Usage

define_missingness(
  variable,
  formula,
  link = c("identity", "logit"),
  baseline = FALSE,
  monotone = FALSE
)

Arguments

variable

Variable that may be missing. A single non-empty string.

formula

Missingness formula, given as a number, a string, or an unquoted expression over the data columns. It is read as a probability under the identity link and as log odds under the logit link. It is stored as text and evaluated row by row.

link

Scale the formula is stated on, one of "identity" (the default) or "logit".

baseline

Replace every period's draw for a unit with its first period's draw, so the unit is either always or never missing. A single flag, defaulting to FALSE. It needs id and period in missingness_matrix().

monotone

Once missing, remain missing at every later period. A single flag, defaulting to FALSE. It needs id and period in missingness_matrix().

Value

A one-row simulab_missing_spec base data.frame with the character columns variable, formula and link and the logical columns baseline and monotone.

Examples

define_missingness("outcome", formula = "0.2")
#>   variable formula     link baseline monotone
#> 1  outcome     0.2 identity    FALSE    FALSE