ProjectionTest: Carry out a test of MCAR in a contingency table, given...

In MCARtest: Optimal Nonparametric Testing of Missing Completely at Random

Carry out a test of MCAR in a contingency table, given incomplete observations.

Description

Carry out a test of MCAR in a contingency table, given incomplete observations.

Usage

ProjectionTest(pSh, nS, bS, M, B)

Arguments

pSh	A sequence of empirical mass functions calculated using incomplete observations.
nS	A sequence of integers giving the numbers of incomplete observations used to calculate pSh.
bS	A binary matrix specifying the set of observation patterns. Each row encodes a single pattern.
M	A vector of positive integers giving the alphabet sizes of the discrete variables.
B	An integer giving the number of bootstrap samples to be used to calibrate the test.

Value

The p-value the Monte Carlo test described in \insertCiteBS2022;textualMCARtest.

The value of the test statistic R().

References

\insertRef

BS2022MCARtest

Examples

bS=matrix(c(1,1,0, 1,0,1, 0,1,1),byrow=TRUE,ncol=3) # Our canonical 3d example
M=c(2,2,2)
nS=c(200,200,200)

pS=c(0.125,0.375,0.375,0.125,0.250,0.250,0.250,0.250,0.100,0.400,0.400,0.100)
P12=pS[1:4]; P13=pS[5:8]; P23=pS[9:12]
X12=t(rmultinom(1,size=nS[1],prob=P12)/nS[1])
X13=t(rmultinom(1,size=nS[2],prob=P13)/nS[2])
X23=t(rmultinom(1,size=nS[3],prob=P23)/nS[3])
pSh=cbind(X12,X13,X23)

ProjectionTest(pSh,nS,bS,M,99)

MCARtest documentation built on Oct. 29, 2024, 5:08 p.m.