Hypothesis Test for Pearson Correlation Coefficient

Adjust the cor.test function so that it can define the specific H0 as per your request, that is based on Fisher's Z transformation of the correlation.

Usage

pearsonTest(
  x,
  y,
  h0 = 0,
  conf.level = 0.95,
  alternative = c("two.sided", "less", "greater"),
  ...
)

Arguments

x

(numeric)
one measurement.

y

(numeric)
another measurement.

h0

(numeric)
a specified hypothesized value of the difference between the two correlations, default is 0.

conf.level

(numeric)
significance level for the returned confidence interval and hypothesis.

alternative

(string)
string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less".

...

other arguments to be passed to cor.test().

Value

a named vector contains correlation coefficient (cor), confidence interval(lowerci and upperci), Z statistic (Z) and p-value (pval)

References

NCSS correlation document

See also

cor.test() to see the detailed arguments.

Examples

x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c(2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
pearsonTest(x, y, h0 = 0.5, alternative = "greater")
#> $stat
#>        cor    lowerci    upperci          Z       pval 
#>  0.5711816 -0.1497426  0.8955795  0.2448722  0.4032777 
#> 
#> $method
#> [1] "Pearson's correlation"
#> 
#> $conf.level
#> [1] 0.95
#>