nice_t_test {rempsyc}

Easy t-tests

Description

Easily compute t-test analyses, with effect sizes, and format in publication-ready format. The 95% confidence interval is for the effect size, Cohen's d, both provided by the effectsize package.

Usage

nice_t_test(
  data,
  response,
  group = NULL,
  correction = "none",
  paired = FALSE,
  verbose = TRUE,
  ...
)

Arguments

data

The data frame.

response

The dependent variable.

group

The group for the comparison.

correction

What correction for multiple comparison to apply, if any. Default is "none" and the only other option (for now) is "bonferroni".

paired

Whether to use a paired t-test.

verbose

Whether to display the Welch test warning or not.

...

Further arguments to be passed to the t.test() function (e.g., to use Student instead of Welch test, to change from two-tail to one-tail, or to do a paired-sample t-test instead of independent samples).

Details

This function relies on the base R t.test() function, which uses the Welch t-test per default (see why here: https://daniellakens.blogspot.com/2015/01/always-use-welchs-t-test-instead-of.html). To use the Student t-test, simply add the following argument: var.equal = TRUE.

Note that for paired t tests, you need to use paired = TRUE, and you also need data in "long" format rather than wide format (like for the ToothGrowth data set). In this case, the group argument refers to the participant ID for example, so the same group/participant is measured several times, and thus has several rows. Note also that R >= 4.4.0 has stopped supporting the paired argument for the formula method used internally here.

For the easystats equivalent, use: report::report() on the t.test() object.

Value

A formatted dataframe of the specified model, with DV, degrees of freedom, t-value, p-value, the effect size, Cohen's d, and its 95% confidence interval lower and upper bounds.

See Also

Tutorial: https://rempsyc.remi-theriault.com/articles/t-test

Examples

# Make the basic table
nice_t_test(
  data = mtcars,
  response = "mpg",
  group = "am"
)

# Multiple dependent variables at once
nice_t_test(
  data = mtcars,
  response = names(mtcars)[1:7],
  group = "am"
)

# Can be passed some of the regular arguments
# of base [t.test()]

# Student t-test (instead of Welch)
nice_t_test(
  data = mtcars,
  response = "mpg",
  group = "am",
  var.equal = TRUE
)

# One-sided instead of two-sided
nice_t_test(
  data = mtcars,
  response = "mpg",
  group = "am",
  alternative = "less"
)

# One-sample t-test
nice_t_test(
  data = mtcars,
  response = "mpg",
  mu = 10
)

# Make sure cases appear in the same order for
# both levels of the grouping factor