delete_MNAR_one_group: Create MNAR values by deleting values in one of two groups

In missMethods: Methods for Missing Data

Create MNAR values by deleting values in one of two groups

Description

Create missing not at random (MNAR) values by deleting values in one of two groups in a data frame or a matrix

Usage

delete_MNAR_one_group(
  ds,
  p,
  cols_mis,
  cutoff_fun = median,
  prop = 0.5,
  use_lpSolve = TRUE,
  ordered_as_unordered = FALSE,
  n_mis_stochastic = FALSE,
  ...,
  miss_cols,
  stochastic
)

Arguments

ds	A data frame or matrix in which missing values will be created.
p	A numeric vector with length one or equal to length cols_mis; the probability that a value is missing.
cols_mis	A vector of column names or indices of columns in which missing values will be created.
cutoff_fun	Function that calculates the cutoff values in the cols_ctrl.
prop	Numeric of length one; (minimum) proportion of rows in group 1 (only used for unordered factors).
use_lpSolve	Logical; should lpSolve be used for the determination of groups, if cols_ctrl[i] is an unordered factor.
ordered_as_unordered	Logical; should ordered factors be treated as unordered factors.
n_mis_stochastic	Logical, should the number of missing values be stochastic? If n_mis_stochastic = TRUE, the number of missing values for a column with missing values cols_mis[i] is a random variable with expected value nrow(ds) * p[i]. If n_mis_stochastic = FALSE, the number of missing values will be deterministic. Normally, the number of missing values for a column with missing values cols_mis[i] is round(nrow(ds) * p[i]). Possible deviations from this value, if any exists, are documented in Details.
...	Further arguments passed to cutoff_fun.
miss_cols	Deprecated, use cols_mis instead.
stochastic	Deprecated, use n_mis_stochastic instead.

Details

The functions delete_MNAR_one_group and delete_MAR_one_group are sisters. The only difference between these two functions is the column that controls the generation of missing values. In delete_MAR_one_group a separate column cols_ctrl[i] controls the generation of missing values in cols_mis[i]. In contrast, in delete_MNAR_one_group the generation of missing values in cols_mis[i] is controlled by cols_mis[i] itself. All other aspects are identical for both functions. Therefore, further details can be found in delete_MAR_one_group.

Value

An object of the same class as ds with missing values.

References

Santos, M. S., Pereira, R. C., Costa, A. F., Soares, J. P., Santos, J., & Abreu, P. H. (2019). Generating Synthetic Missing Data: A Review by Missing Mechanism. IEEE Access, 7, 11651-11667

See Also

delete_MAR_one_group

Other functions to create MNAR: delete_MNAR_1_to_x(), delete_MNAR_censoring(), delete_MNAR_rank()

Examples

ds <- data.frame(X = 1:20, Y = 101:120)
delete_MNAR_one_group(ds, 0.2, "X")

missMethods documentation built on Sept. 16, 2022, 5:08 p.m.