intermediate.corr.BO: Computes an intermediate normal correlation matrix for any combination of binary and ordinal variables given the specified correlation matrix

Description

Computes an intermediate normal correlation matrix for any combination of binary and ordinal variables before dichotomization/ordinalization given the specified correlation matrix as formulated in Ferrari and Barbiero (2012).

Usage

intermediate.corr.BO(n.B, n.O, prop.vec = NULL, prop.list = NULL, corr.vec = NULL, 
corr.mat = NULL)

Arguments

n.B

Number of binary variables.

n.O

Number of ordinal variables.

prop.vec

Probability vector for binary variables.

prop.list

A list of probability vectors for ordinal variables.

corr.vec

Vector of elements below the diagonal of correlation matrix ordered column-wise.

corr.mat

Specified correlation matrix.

Value

A correlation matrix of size (n.B+n.O)*(n.B+n.O).

References

Ferrari, P.A. and Barbiero, A. (2012). Simulating ordinal data. Multivariate Behavioral Research, 47(4), 566-589.

Barbiero, A. and Ferrari, P.A. (2015). GenOrd: Simulation of ordinal and discrete variables with given correlation matrix and marginal distributions. http://www.cran.r-project.org/web/packages/GenOrd.

Examples

Run this code

# NOT RUN {
n.B=1
n.O=2
prop.vec=0.7
prop.list=list(cumsum(c(0.30, 0.40)), cumsum(c(0.4, 0.2, 0.3)))
corr.mat=matrix ( c(
1.0000000, 0.1767231, 0.3006186,
0.1767231, 1.0000000, -0.139923,
0.3006186, -0.1399230, 1.0000000),3,3)
intmatBO=intermediate.corr.BO(n.B,n.O,prop.vec,prop.list,corr.vec=NULL, 
corr.mat)

n.B=1
n.O=1
prop.vec<-c(0.3)
prop.list<-list(c(0.3,0.6))
corr.mat=matrix(c(1,0.2,0.1,0.2,1,0.5,0.1,0.5,1),3,3)
intmatBO=intermediate.corr.BO(n.B,n.O,prop.vec,prop.list,corr.vec=NULL, 
corr.mat)

n.B=2
prop.vec=c(0.4,0.7)
corr.mat=matrix(c(1,-0.3,-0.3,1),2,2)
intmatBB=intermediate.corr.BO(n.B,n.O=0,prop.vec,prop.list=NULL,corr.vec=NULL, 
corr.mat)

#See Tetra.Corr.BB in R package BinNonNor 
#Tetra.Corr.BB(n.BB=2,prop.vec=c(0.4,0.7),corr.vec=NULL,corr.mat=corr.mat)

n.B=0
n.O=2
prop.list=list(cumsum(c(0.30, 0.40)), cumsum(c(0.4,0.2,0.3)))
corr.mat=matrix(c(1.0000000, -0.139923,-0.139923,1.0000000),2,2)
intmatOO=intermediate.corr.BO(n.B,n.O,prop.vec=NULL,prop.list,corr.vec=NULL, 
corr.mat)

#See IntermediateOO(plist, OOCorrMat) in R package OrdNor
#IntermediateOO(plist=list(cumsum(c(0.30,0.40)),cumsum(c(0.4,0.2,0.3))), 
OOCorrMat=corr.mat)
# }