Plot test for association between paired samples

Source: R/ggcortest.R

Visualise test for association between paired samples, using Pearson's product moment correlation coefficient.

ggcortest(t, colaccept="lightskyblue1", colreject="grey94", colstat="navy")

Arguments

t

a list result of cor.test of "htest" class
colaccept

color the acceptance area of the test
colreject

color for the rejection area of the test
colstat

color for the test statistic vline

Examples


corr_test <- cor.test(iris$Sepal.Length, iris$Sepal.Width)
corr_test
#> 
#> 	Pearson's product-moment correlation
#> 
#> data:  iris$Sepal.Length and iris$Sepal.Width
#> t = -1.4403, df = 148, p-value = 0.1519
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#>  -0.27269325  0.04351158
#> sample estimates:
#>        cor 
#> -0.1175698 
#> 
ggcortest(corr_test)