Nothing
np.cor.test <-
function(x, y, z = NULL,
alternative = c("two.sided", "less", "greater"),
rho = 0, independent = FALSE, partial = TRUE,
R = 9999, parallel = FALSE, cl = NULL,
perm.dist = TRUE, na.rm = TRUE){
# Nonparametric Tests of Correlation Coefficients
# Nathaniel E. Helwig (helwig@umn.edu)
# last updated: 2023-04-13
### check x and y
x <- as.numeric(x)
y <- as.numeric(y)
n <- length(x)
if(length(y) != n) stop("Inputs 'x' and 'y' must have same length.")
### check for missing data
if(na.rm){
x <- na.omit(x)
y <- na.omit(y)
if(!is.null(z)) z <- na.omit(z)
}
### check z
if(!is.null(z)){
z <- cbind(1, z)
if(nrow(z) != n) stop("Input 'z' is incompatible with inputs 'x' and 'y'.")
zsvd <- svd(z, nv = 0)
x <- x - zsvd$u %*% crossprod(zsvd$u, x)
if(partial) y <- y - zsvd$u %*% crossprod(zsvd$u, y)
}
### permutation test
pt <- rand.test.cor(x = x, y = y,
alternative = alternative,
rho = rho, independent = independent,
R = R, parallel = parallel, cl = cl,
perm.dist = perm.dist)
### correct se?
if(independent && !is.null(z)){
correct <- sqrt((n - ncol(z) - 1) / (n - 2))
pt$statistic <- pt$statistic * correct
if(perm.dist) pt$perm.dist <- pt$perm.dist * correct
}
### return results
class(pt) <- "np.cor.test"
return(pt)
} # end np.cor.test.R
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