R: Multivariate amputation under a MCAR mechanism

ampute.mcar {mice} | R Documentation

## Multivariate amputation under a MCAR mechanism

### Description

This function creates a missing data indicator for each pattern, based on a MCAR missingness mechanism. The function is used in the multivariate amputation function `ampute`.

### Usage

    ampute.mcar(P, patterns, prop)

### Arguments

`P` | A vector containing the pattern numbers of the cases' candidates. For each case, a value between 1 and #patterns is given. For example, a case with value 2 is candidate for missing data pattern 2.
`patterns` | A matrix of size #patterns by #variables where `0` indicates a variable should have missing values and `1` indicates a variable should remain complete. The user may specify as many patterns as desired. One pattern (a vector) is also possible. Could be the result of `ampute.default.patterns`, default will be a square matrix of size #variables where each pattern has missingness on one variable only.
`prop` | A scalar specifying the proportion of missingness. Should be a value between 0 and 1. Default is a missingness proportion of 0.5.

### Value

A list containing vectors with `0` if a case should be made missing and `1` if a case should remain complete. The first vector refers to the first pattern, the second vector to the second pattern, etcetera.

### Author(s)

Rianne Schouten, 2016

### See Also

`ampute`

[Package mice version 3.13.0 Index]