correlation.bound.check {PoisBinNonNor} | R Documentation |
Checks if the pairwise correlation among variables are within the feasible range
Description
This function checks if there are range violations among correlation of Poisson-Poisson, Poisson-binary, Poisson-continuous, binary-binary, binary-continuous, and continuous-continuous combinations.
Usage
correlation.bound.check(n.P, n.B, n.C, lambda.vec = NULL, prop.vec = NULL,
coef.mat = NULL, 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. |
lambda.vec |
Rate vector for Poisson variables. |
prop.vec |
Proportion vector for binary variables. |
coef.mat |
Matrix of coefficients produced from |
corr.vec |
Vector of elements below the diagonal of correlation matrix ordered column-wise. |
corr.mat |
Specified correlation matrix. |
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
validation.corr
, correlation.limits
Examples
## Not run:
n.P<-1
n.B<-1
n.C<-1
lambda.vec<-c(1)
prop.vec<-c(0.3)
coef.mat<-matrix(c(-0.3137491,0.8263239,0.3137491,0.0227066),4,1,byrow=F)
corr.mat=matrix(c(1,0.2,0.1,0.2,1,0.5,0.1,0.5,1),3,3)
correlation.bound.check(n.P,n.B,n.C,lambda.vec,prop.vec,coef.mat,corr.vec=NULL,
corr.mat)
n.P<-2
n.B<-2
n.C<-2
lambda.vec<-c(1,2)
prop.vec<-c(0.3,0.5)
coef.mat<-matrix(c(
-0.3137491, 0.0000000,
0.8263239, 1.0857433,
0.3137491, 0.0000000,
0.0227066, -0.0294495),4,2,byrow=F)
corr.mat=matrix(0.8,6,6)
diag(corr.mat)=1
correlation.bound.check(n.P,n.B,n.C,lambda.vec,prop.vec,coef.mat,corr.vec=NULL,
corr.mat)
## End(Not run)