Easy t-tests

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.

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.

Usage

nice_t_test(
  data,
  response,
  group = NULL,
  correction = "none",
  warning = 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".
warning: 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).

Examples

# Make the basic table
nice_t_test(
  data = mtcars,
  response = "mpg",
  group = "am"
)
#> Using Welch t-test (base R's default; cf. https://doi.org/10.5334/irsp.82).
#> For the Student t-test, use `var.equal = TRUE`. 
#>  
#>  
#>   Dependent Variable         t       df           p         d  CI_lower
#> 1                mpg -3.767123 18.33225 0.001373638 -1.477947 -2.265973
#>     CI_upper
#> 1 -0.6705686

# Multiple dependent variables at once
nice_t_test(
  data = mtcars,
  response = names(mtcars)[1:7],
  group = "am"
)
#> Using Welch t-test (base R's default; cf. https://doi.org/10.5334/irsp.82).
#> For the Student t-test, use `var.equal = TRUE`. 
#>  
#>  
#>   Dependent Variable         t       df            p          d   CI_lower
#> 1                mpg -3.767123 18.33225 1.373638e-03 -1.4779471 -2.2659731
#> 2                cyl  3.354114 25.85363 2.464713e-03  1.2084550  0.4315896
#> 3               disp  4.197727 29.25845 2.300413e-04  1.4452210  0.6417834
#> 4                 hp  1.266189 18.71541 2.209796e-01  0.4943081 -0.2260466
#> 5               drat -5.646088 27.19780 5.266742e-06 -2.0030843 -2.8592770
#> 6                 wt  5.493905 29.23352 6.272020e-06  1.8924060  1.0300224
#> 7               qsec  1.287845 25.53421 2.093498e-01  0.4656285 -0.2532864
#>     CI_upper
#> 1 -0.6705686
#> 2  1.9683146
#> 3  2.2295592
#> 4  1.2066992
#> 5 -1.1245498
#> 6  2.7329218
#> 7  1.1770176

# 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
)
#> Using Student t-test. 
#>  
#>  
#>   Dependent Variable         t df            p         d  CI_lower   CI_upper
#> 1                mpg -4.106127 30 0.0002850207 -1.477947 -2.265973 -0.6705686

# One-sided instead of two-sided
nice_t_test(
  data = mtcars,
  response = "mpg",
  group = "am",
  alternative = "less"
)
#> Using Welch t-test (base R's default; cf. https://doi.org/10.5334/irsp.82).
#> For the Student t-test, use `var.equal = TRUE`. 
#>  
#>  
#>   Dependent Variable         t       df            p         d  CI_lower
#> 1                mpg -3.767123 18.33225 0.0006868192 -1.477947 -2.265973
#>     CI_upper
#> 1 -0.6705686

# One-sample t-test
nice_t_test(
  data = mtcars,
  response = "mpg",
  mu = 10
)
#> Using Welch t-test (base R's default; cf. https://doi.org/10.5334/irsp.82).
#> For the Student t-test, use `var.equal = TRUE`. 
#>  
#>  Using one-sample t-test. 
#>  
#>  
#>   Dependent Variable        t df            p        d CI_lower CI_upper
#> 1                mpg 9.470995 31 1.154598e-10 1.674251  1.12797 2.208995

# Paired t-test instead of independent samples
nice_t_test(
  data = ToothGrowth,
  response = "len",
  group = "supp",
  paired = TRUE
)
#> Using paired t-test. 
#>  
#>  
#>   Dependent Variable        t df           p         d  CI_lower  CI_upper
#> 1                len 3.302585 29 0.002549842 0.6029668 0.2088153 0.9883436
# Make sure cases appear in the same order for
# both levels of the grouping factor

Usage

Arguments

See also

Examples