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Last data update: 2014.03.03

R: Creates artificial missing at random missingness

makemar

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

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

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(CALIBERrfimpute)
Loading required package: mice
Loading required package: Rcpp
mice 2.25 2015-11-09
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/CALIBERrfimpute/makemar.Rd_%03d_medium.png", width=480, height=480)
> ### Name: makemar
> ### Title: Creates artificial missing at random missingness
> ### Aliases: makemar
> 
> ### ** 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 
> # y x1 x2 x3 x4 
> # 0 11 10  0  0 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>