intermediate.corr.BB: Computes an intermediate normal correlation matrix for binary...

In PoisBinNonNor: Data Generation with Poisson, Binary and Continuous Components

Description

Computes an intermediate normal correlation matrix for binary variables before dichotomization given the specified correlation matrix.

Usage

intermediate.corr.BB(n.P, n.B, n.C, prop.vec, corr.vec = NULL, corr.mat = NULL)

Arguments

n.P	Number of Poisson variables.
n.B	Number of binary variables.
n.C	Number of continuous variables.
prop.vec	Proportion vector for binary 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.B.

References

Demirtas, H., Hedeker, D., and Mermelstein, R.J. (2012). Simulation of massive public health data by power polynomials. Statistics in Medicine, 31(27), 3337-3346.

See Also

intermediate.corr.PB, intermediate.corr.BC

Examples

## Not run: 
n.P<-2
n.B<-2
n.C<-2
prop.vec=c(0.4,0.7)
corr.vec = NULL
corr.mat=matrix(c(1.0,-0.3,-0.3,-0.3,-0.3,-0.3,
-0.3,1.0,-0.3,-0.3,-0.3,-0.3,
-0.3,-0.3,1.0,0.4,0.5,0.6,
-0.3,-0.3,0.4,1.0,0.7,0.8,
-0.3,-0.3,0.5,0.7,1.0,0.9,
-0.3,-0.3,0.6,0.8,0.9,1.0),6,by=TRUE)

intmatBB=intermediate.corr.BB(n.P,n.B,n.C,prop.vec,corr.vec=NULL,corr.mat)
intmatBB

## End(Not run)

PoisBinNonNor documentation built on March 22, 2021, 9:07 a.m.