correlation.bound.check: Checks if the pairwise correlation among variables are within...

In BinNonNor: Data Generation with Binary and Continuous Non-Normal Components

Description

This function checks if there are range violations among correlation of binary-binary, binary-continuous, and continuous-continuous combinations.

Usage

correlation.bound.check(n.BB, n.NN, prop.vec = NULL, corr.vec = NULL, 
       corr.mat = NULL, coef.mat = NULL)

Arguments

n.BB	Number of binary variables.
n.NN	Number of continuous non-normal variables.
prop.vec	Probability vector for binary variables.
corr.vec	Specified correlation vector.
corr.mat	Specified correlation matrix.
coef.mat	Matrix of coefficients produced from fleishman.coef.

Value

The function returns TRUE if no specification problem is encountered. Otherwise, it returns an error message.

References

Demirtas, H. and Hedeker, D. (2011). A practical way for computing approximate lower and upper correlation bounds. The American Statistician, 65(2), 104-109.

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

fleishman.coef, correlation.limits, validation.corr

Examples

prop.vec=c(0.4,0.7)
n.BB=2
n.NN=4
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,byrow=TRUE)

coef.mat=matrix(c(
 -0.31375,  0.00000,  0.10045, -0.10448,
  0.82632,  1.08574,  1.10502,  0.98085,
  0.31375,  0.00000, -0.10045,  0.10448,
  0.02271, -0.02945, -0.04001,  0.00272),4,byrow=TRUE)

correlation.bound.check(n.BB,n.NN,prop.vec,corr.vec=NULL,corr.mat,coef.mat)

cor.mat.BB=corr.mat[1:2,1:2]
correlation.bound.check(n.BB,n.NN=0,prop.vec,corr.vec=NULL,corr.mat=cor.mat.BB,
coef.mat=NULL)

cor.mat.NN=corr.mat[3:6,3:6]
correlation.bound.check(n.BB=0,n.NN,prop.vec=NULL,corr.vec=NULL,corr.mat=cor.mat.NN,
coef.mat)

n.BB=1
prop.vec=0.5
corr.mat=diag(n.BB)
correlation.bound.check(n.BB,n.NN=0,prop.vec,corr.vec=NULL,corr.mat=corr.mat,
coef.mat=NULL)

## Not run: 
cor.mat.NNnew=cor.mat.NN
cor.mat.NNnew[1,2]=0.92
cor.mat.NNnew[2,1]=0.92
correlation.bound.check(n.BB=0,n.NN,prop.vec=NULL,corr.vec=NULL,corr.mat=cor.mat.NNnew,
coef.mat)

## End(Not run)

BinNonNor documentation built on March 22, 2021, 9:08 a.m.