corrCompTest: Carry out a test of MCAR checking compatibility of...

In MCARtest: Optimal Nonparametric Testing of Missing Completely at Random

Carry out a test of MCAR checking compatibility of correlation matrices.

Description

This is the implementation of Algorithm 1 in \insertCiteBB2024;textualMCARtest.

Usage

corrCompTest(X, B)

Arguments

X	The dataset with incomplete data.
B	The bootstrap sample B for the bootstrap test.

Value

The p-value of the test of MCAR based on correlation matrices, as outlined in Algorithm 1 in \insertCiteBB2024;textualMCARtest.

References

\insertRef

BB2024MCARtest

Examples

library(MASS)
alpha = 0.05
B = 20
m = 500

SigmaS=list() #Random 2x2 correlation matrices (necessarily consistent)
for(j in 1:3){
x=runif(2,min=-1,max=1); y=runif(2,min=-1,max=1)
SigmaS[[j]]=cov2cor(x%*%t(x) + y%*%t(y))
}

X1 = mvrnorm(m, c(0,0), SigmaS[[1]])
X2 = mvrnorm(m, c(0,0), SigmaS[[2]])
X3 = mvrnorm(m, c(0,0), SigmaS[[3]])
columns = c("X1","X2","X3")
X = data.frame(matrix(nrow = 3*m, ncol = 3))
X[1:m, c("X1", "X2")] = X1
X[(m+1):(2*m), c("X2", "X3")] = X2
X[(2*m+1):(3*m), c("X1", "X3")] = X3
X = as.matrix(X)

corrCompTest(X, B)

MCARtest documentation built on June 26, 2025, 5:08 p.m.