R/permTestCor.R

In CarletonStats: Functions for Statistics Classes at Carleton College

#' Permutation test for the correlation of two variables.
#'
#' Hypothesis test for a correlation of two variables. The null hypothesis is
#' that the population correlation is 0.
#'
#' Perform a permutation test to test \eqn{latex}{H_0: \rho = 0}, where
#' \eqn{latex}{\rho}is the population correlation. The rows of the second
#' variable are permuted and the correlation is re-computed.
#'
#' The mean and standard error of the permutation distribution is printed as
#' well as a P-value.
#'
#' Observations with missing values are removed.
#'
#' @aliases permTestCor permTestCor.default permTestCor.formula
#' @param x a numeric vector.
#' @param y a numeric vector.
#' @param B the number of resamples to draw (positive integer greater than 2).
#' @param seed optional argument to \code{\link{set.seed}}
#' @param alternative alternative hypothesis. Options are \code{"two.sided"},
#' \code{"less"} or \code{"greater"}.
#' @param plot.hist a logical value. If \code{TRUE}, plot the distribution of
#' the correlations obtained from each resample.
#' @param plot.qq a logical value. If \code{TRUE}, plot the normal
#' quantile-quantile plot of the correlations obtained from each resample.
#' @param x.name Label for variable x
#' @param y.name Label for variable y
#' @param formula a formula \code{y ~ x} where \code{x, y} are numeric vectors.
#' @param data a data frame that contains the variables given in the formula.
#' @param subset an optional expression indicating what observations to use.
#' @param xlab an optional character string for the x-axis label
#' @param ylab an optional character string for the y-axis label
#' @param title an optional character string giving the plot title
#' @param \dots further arguments to be passed to or from methods.
#' @return Returns invisibly a vector of the correlations obtained by the
#' randomization.
#' @author Laura Chihara
#' @references Tim Hesterberg's website:
#' \url{https://www.timhesterberg.net/bootstrap-and-resampling}
#' @keywords permutation test randomization resampling correlation
#' @examples
#'
#' plot(states03$HSGrad, states03$TeenBirths)
#' cor(states03$HSGrad, states03$TeenBirths)
#'
#' permTestCor(states03$HSGrad, states03$TeenBirths)
#' permTestCor(TeenBirths ~ HSGrad, data = states03)
#'
#' @export

permTestCor <-
function(x,  ...)
{
  UseMethod("permTestCor")

}