cmenet (version 0.1.2)

full.model.mtx: Generate full model matrix for MEs and CMEs

Description

full.model.mtx returns the full model matrix for main effects (MEs) and conditional main effects (CMEs).

Usage

full.model.mtx(xme)

Arguments

xme

An \(n\) x \(p\) binary model matrix (\(n\) observations, \(p\) binary MEs).

Value

model.mtx

An \(n\) x (\(p\)+4*choose(\(p\),2)) full model matrix for MEs and CMEs.

cme.mtx

An \(n\) x (4*choose(\(p\),2)) model matrix for only CMEs.

Examples

# NOT RUN {
library(MASS)
n <- 50 #number of observations
p <- 50 #number of main effects

## Simulate model matrix for MEs and CMEs
set.seed(1)
rho <- 0 #correlation
ones <- matrix(1,p,p)
covmtx <- rho*ones+(1-rho)*diag(p)
latmtx <- mvrnorm(n,p,mu=rep(0,p),Sigma=covmtx) #equicorrelated cov. matrix
memtx <- (latmtx>=0)-(latmtx<0) #simulate model matrix for MEs
model.mtx <- full.model.mtx(memtx)$model.mtx #generate model matrix for MEs and CMEs

# }