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Create reports for htest objects (t.test(), cor.test(), etc.).

Usage

# S3 method for htest
report(x, ...)

# S3 method for htest
report_effectsize(x, ...)

# S3 method for htest
report_table(x, ...)

# S3 method for htest
report_statistics(x, table = NULL, ...)

# S3 method for htest
report_parameters(x, table = NULL, ...)

# S3 method for htest
report_model(x, table = NULL, ...)

# S3 method for htest
report_info(x, effectsize = NULL, ...)

# S3 method for htest
report_text(x, table = NULL, ...)

Arguments

x

Object of class htest.

...

Arguments passed to or from other methods.

table

Provide the output of report_table() to avoid its re-computation.

effectsize

Provide the output of report_effectsize() to avoid its re-computation.

Value

An object of class report().

Examples

report(t.test(iris$Sepal.Width, iris$Sepal.Length))
#> Effect sizes were labelled following Cohen's (1988) recommendations.
#> 
#> The Welch Two Sample t-test testing the difference between iris$Sepal.Width and iris$Sepal.Length (mean of x = 3.06, mean of y = 5.84) suggests that the effect is negative, statistically significant, and large (difference = -2.79, 95% CI [-2.94, -2.64], t(225.68) = -36.46, p < .001; Cohen's d = -4.21, 95% CI [-4.66, -3.76])
report(t.test(iris$Sepal.Width, iris$Sepal.Length, var.equal = TRUE))
#> Effect sizes were labelled following Cohen's (1988) recommendations.
#> 
#> The Two Sample t-test testing the difference between iris$Sepal.Width and iris$Sepal.Length (mean of x = 3.06, mean of y = 5.84) suggests that the effect is negative, statistically significant, and large (difference = -2.79, 95% CI [-2.94, -2.64], t(298) = -36.46, p < .001; Cohen's d = -4.21, 95% CI [-4.61, -3.80])
report(t.test(mtcars$mpg ~ mtcars$vs))
#> Effect sizes were labelled following Cohen's (1988) recommendations.
#> 
#> The Welch Two Sample t-test testing the difference of mtcars$mpg by mtcars$vs (mean in group 0 = 16.62, mean in group 1 = 24.56) suggests that the effect is negative, statistically significant, and large (difference = -7.94, 95% CI [-11.46, -4.42], t(22.72) = -4.67, p < .001; Cohen's d = -1.70, 95% CI [-2.55, -0.82])
report(t.test(mtcars$mpg, mtcars$vs, paired = TRUE))
#> Warning: 'y' is numeric but has only 2 unique values.
#> If this is a grouping variable, convert it to a factor.
#> Effect sizes were labelled following Cohen's (1988) recommendations.
#> 
#> The Paired t-test testing the difference between mtcars$mpg and mtcars$vs (mean difference = 19.65) suggests that the effect is positive, statistically significant, and large (difference = 19.65, 95% CI [17.60, 21.71], t(31) = 19.49, p < .001; Cohen's d = 3.45, 95% CI [2.56, 4.43])
report(t.test(iris$Sepal.Width, mu = 1))
#> Effect sizes were labelled following Cohen's (1988) recommendations.
#> 
#> The One Sample t-test testing the difference between iris$Sepal.Width (mean = 3.06) and mu = 1 suggests that the effect is positive, statistically significant, and large (difference = 2.06, 95% CI [2.99, 3.13], t(149) = 57.81, p < .001; Cohen's d = 4.72, 95% CI [4.17, 5.29])