permTestCor {CarletonStats} | R Documentation |
Hypothesis test for a correlation of two variables. The null hypothesis is that the population correlation is 0.
permTestCor(x, ...) ## Default S3 method: permTestCor(x, y, B = 999, alternative = "two.sided", plot.hist = TRUE, legend.loc = "topright", plot.qq = FALSE, x.name = deparse(substitute(x)), y.name = deparse(substitute(y)), ...) ## S3 method for class 'formula' permTestCor(formula, data, subset, ...)
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 |
plot.hist |
a logical value. If |
legend.loc |
location of the legend on the histogram. Options are
|
plot.qq |
a logical value. If |
x.name |
Label for variable x |
y.name |
Label for variable y |
formula |
a formula |
data |
a data frame that contains the variables given in the formula. |
subset |
an optional expression indicating what observations to use. |
Perform a permutation test to test H_0: ρ = 0, where ρis 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.
Returns invisibly a vector of the correlations obtained by the randomization.
default
: Permutation test for the correlation of two variables.
formula
: Permutation test for the correlation of two variables.
Laura Chihara
Tim Hesterberg's website: http://www.timhesterberg.net/bootstrap
plot(states03$HSGrad, states03$TeenBirths) cor(states03$HSGrad, states03$TeenBirths) permTestCor(states03$HSGrad, states03$TeenBirths) permTestCor(TeenBirths ~ HSGrad, data = states03)