BinNonNor (version 1.5.3)

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

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

# NOT RUN {
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)
# }