makemar {CALIBERrfimpute}R Documentation

Creates artificial missing at random missingness

Description

Introduces missingness into x1 and x2 into a data.frame of the format produced by simdata, for use in the simulation study. The probability of missingness depends on the logistic of the fully observed variables y and x3; hence it is missing at random but not missing completely at random.

Usage

makemar(simdata, prop = 0.2)

Arguments

simdata

simulated dataset created by simdata.

prop

proportion of missing values to be introduced in x1 and x2.

Details

This function is used for simulation and testing.

Value

A data.frame with columns:

y

dependent variable, based on the model y = x1 + x2 + x3 + normal error

x1

partially observed continuous variable

x2

partially observed continuous or binary (factor) variable

x3

fully observed continuous variable

x4

variable not in the model to predict y, but associated with x1, x2 and x3; used as an auxiliary variable in imputation

See Also

simdata

Examples

set.seed(1)
mydata <- simdata(n=100)
mymardata <- makemar(mydata, prop=0.1)
# Count the number of missing values
sapply(mymardata, function(x){sum(is.na(x))})
# y x1 x2 x3 x4 
# 0 11 10  0  0 

[Package CALIBERrfimpute version 1.0-5 Index]