Description Usage Arguments Value Author(s) References Examples
It computes the asymptotic sampling covariance matrix of a correlation/covariance matrix under the assumption of multivariate normality.
1 2 3 
x 
A correlation/covariance matrix or a list of
correlation/covariance matrices. 
n 
Sample size or a vector of sample sizes 
cor.analysis 
Logical. The output is either a correlation or covariance matrix. 
dropNA 
Logical. If it is 
as.matrix 
Logical. If it is 
acov 
If it is 
suppressWarnings 
Logical. If 
silent 
Logical. Argument to be passed to

run 
Logical. If 
... 
Further arguments to be passed to 
An asymptotic covariance matrix of the vectorized
correlation/covariance matrix or a list of these matrices. If
as.matrix
=TRUE
and x
is a list of matrices, the output
is a stacked matrix.
Mike W.L. Cheung <[email protected]>
Cheung, M. W.L., & Chan, W. (2004). Testing dependent correlation coefficients via structural equation modeling. Organizational Research Methods, 7, 206223.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ## Not run:
C1 < matrix(c(1,0.5,0.4,0.5,1,0.2,0.4,0.2,1), ncol=3)
asyCov(C1, n=100)
## Data with missing values
C2 < matrix(c(1,0.4,NA,0.4,1,NA,NA,NA,NA), ncol=3)
C3 < matrix(c(1,0.2,0.2,1), ncol=2)
## Output is a list of asymptotic covariance matrices
asyCov(list(C1,C2,C3), n=c(100,50,50), dropNA=TRUE, as.matrix=FALSE)
## Output is a stacked matrix of asymptotic covariance matrices
asyCov(list(C1,C2), n=c(100,50), as.matrix=TRUE)
## Output is a stacked matrix of asymptotic covariance matrices
asyCov(list(C3,C3), n=c(100,50), as.matrix=TRUE)
## End(Not run)

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