# delete_MNAR_one_group: Create MNAR values by deleting values in one of two groups In missMethods: Methods for Missing Data

## Description

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

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```delete_MNAR_one_group( ds, p, cols_mis, cutoff_fun = median, prop = 0.5, use_lpSolve = TRUE, ordered_as_unordered = FALSE, stochastic = FALSE, ..., miss_cols ) ```

## 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. `stochastic` Logical; see details. `...` Further arguments passed to `cutoff_fun`. `miss_cols` Deprecated, use cols_mis 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

`delete_MAR_one_group`
Other functions to create MNAR: `delete_MNAR_1_to_x()`, `delete_MNAR_censoring()`, `delete_MNAR_rank()`
 ```1 2``` ```ds <- data.frame(X = 1:20, Y = 101:120) delete_MNAR_one_group(ds, 0.2, "X") ```