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Permutation test for the correlation of two variables.

Source: R/permTestCor.R, R/permTestCor.default.R, R/permTestCor.formula.R
permTestCor.Rd

Hypothesis test for a correlation of two variables. The null hypothesis is that the population correlation is 0.

Usage

permTestCor(x, ...)

# Default S3 method
permTestCor(
  x,
  y,
  B = 999,
  alternative = "two.sided",
  plot.hist = TRUE,
  plot.qq = FALSE,
  x.name = deparse(substitute(x)),
  y.name = deparse(substitute(y)),
  xlab = NULL,
  ylab = NULL,
  title = NULL,
  seed = NULL,
  ...
)

# S3 method for class 'formula'
permTestCor(formula, data, subset, ...)

Arguments

x

a numeric vector.

...

further arguments to be passed to or from methods.

y

a numeric vector.

B

the number of resamples to draw (positive integer greater than 2).

alternative

alternative hypothesis. Options are "two.sided", "less" or "greater".

plot.hist

a logical value. If TRUE, plot the distribution of the correlations obtained from each resample.

plot.qq

a logical value. If TRUE, plot the normal quantile-quantile plot of the correlations obtained from each resample.

x.name

Label for variable x

y.name

Label for variable y

xlab

an optional character string for the x-axis label

ylab

an optional character string for the y-axis label

title

an optional character string giving the plot title

seed

optional argument to set.seed

formula

a formula y ~ x where x, y are numeric vectors.

data

a data frame that contains the variables given in the formula.

subset

an optional expression indicating what observations to use.

Value

Returns invisibly a vector of the correlations obtained by the randomization.

Details

Perform a permutation test to test \(latex\), where \(latex\)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.

Methods (by class)

  • permTestCor(default): Permutation test for the correlation of two variables.

  • permTestCor(formula): Permutation test for the correlation of two variables.

References

Tim Hesterberg's website: https://www.timhesterberg.net/bootstrap-and-resampling

Author

Laura Chihara

Examples


plot(states03$HSGrad, states03$TeenBirths)

cor(states03$HSGrad, states03$TeenBirths)
#> [1] -0.6761514

permTestCor(states03$HSGrad, states03$TeenBirths)
#> 
#> 	** Permutation test **
#> 
#>  Permutation test with alternative: two.sided 
#>  Observed correlation between states03$HSGrad ,  states03$TeenBirths : -0.6762 
#>  Mean of permutation distribution: -0.00135 
#>  Standard error of permutation distribution: 0.14573 
#>  P-value:   0.001 
#> 
#> 	*-------------*
#> 

permTestCor(TeenBirths ~ HSGrad, data = states03)
#> 
#> 	** Permutation test **
#> 
#>  Permutation test with alternative: two.sided 
#>  Observed correlation between HSGrad ,  TeenBirths : -0.6762 
#>  Mean of permutation distribution: -0.00553 
#>  Standard error of permutation distribution: 0.1461 
#>  P-value:   0.001 
#> 
#> 	*-------------*
#>