MonteCarloSEM (version 2.0.0)

MCAR.data: Introduces Missing Completely at Random (MCAR) Values into Data Sets.

Description

This function introduces missing values under the Missing Completely at Random (MCAR) mechanism into previously generated data sets (e.g., those produced by sim.skewed() or sim.normal()). Missing values are inserted at random locations according to user specifications and are denoted as "NA" in the resulting files. The modified data sets are saved as new files, preserving the original data sets. In each data file, the first column contains the sample identifiers, while the subsequent columns show actual data with some entries replaced by NA. Additionally, a file named "MCAR_List.dat" is created, listing the names of all data sets to which missing values were introduced.

Usage

MCAR.data(misg = NULL, perct = 10, dataList = "Data_List.dat", f.loc)

Arguments

misg

A numeric vector of 0s and 1s specifying which items will contain missing values. A value of 0 indicates the item will not include missingness, while 1 indicates missing values will be introduced.If omitted, all items are treated as eligible for missingness.

perct

The percentage of missingness to be applied (default = 10 percents).

dataList

The file name containing the list of previously generated data sets (e.g., "Data_List.dat"), either created by this package or by external software.

f.loc

The directory path where both the original data sets and the "dataList" file are located.

Author

Fatih Orcan

Examples

# Step 1: Generate data sets
fc<-fcors.value(nf=3, cors=c(1,.5,.6,.5,1,.4,.6,.4,1))
fl<-loading.value(nf=3, fl.loads=c(.5,.5,.5,0,0,0,0,0,0,0,0,.6,.6,.6,0,0,0,0,0,0,0,0,.4,.4))
floc<-tempdir()
sim.normal(nd=10, ss=100, fcors=fc, loading<-fl,  f.loc=floc)

 # Step 2: Introduce missing values

mis.items<-c(1,1,1,0,0,0,0,0)
dl<-"Data_List.dat"  # must be located in the working directory
MCAR.data(misg = mis.items, perct = 20, dataList = dl, f.loc=floc)