t_test_pairwise function

t-tests, pairwise

Conducts a t-test for every possible pairwise comparison with Holm or Bonferroni correction

t_test_pairwise(
  data = NULL,
  iv_name = NULL,
  dv_name = NULL,
  sigfigs = 3,
  welch = TRUE,
  cohen_d = TRUE,
  cohen_d_w_ci = TRUE,
  adjust_p = "holm",
  bonferroni = NULL,
  mann_whitney = TRUE,
  mann_whitney_exact = FALSE,
  t_test_stats = TRUE,
  sd = FALSE,
  round_p = 3,
  anova = FALSE,
  round_f = 2,
  round_t = 2,
  round_t_test_df = 2
)

Arguments

• data: a data object (a data frame or a data.table)
• iv_name: name of the independent variable
• dv_name: name of the dependent variable
• sigfigs: number of significant digits to round to
• welch: Should Welch's t-tests be conducted? By default, welch = TRUE
• cohen_d: if cohen_d = TRUE, Cohen's d statistics will be included in the output data.table.
• cohen_d_w_ci: if cohen_d_w_ci = TRUE, Cohen's d with 95% CI will be included in the output data.table.
• adjust_p: the name of the method to use to adjust p-values. If adjust_p = "holm", the Holm method will be used; if adjust_p = "bonferroni", the Bonferroni method will be used. By default, adjust_p = "holm"
• bonferroni: The use of this argument is deprecated. Use the 'adjust_p' argument instead. If bonferroni = TRUE, Bonferroni tests will be conducted for t-tests or Mann-Whitney tests.
• mann_whitney: if TRUE, Mann-Whitney test results will be included in the output data.table. If FALSE, Mann-Whitney tests will not be performed.
• mann_whitney_exact: this is the input for the 'exact' argument used in the 'stats::wilcox.test' function, which conducts a Mann-Whitney test. By default, mann_whitney_exact = FALSE. If you want to use the default settings for the 'stats::wilcox.test' function, consider setting mann_whitney_exact = TRUE.
• t_test_stats: if t_test_stats = TRUE, t-test statistic and degrees of freedom will be included in the output data.table. By default, t_test_stats = TRUE
• sd: if sd = TRUE, standard deviations will be included in the output data.table.
• round_p: number of decimal places to which to round p-values (default = 3)
• anova: Should a one-way ANOVA be conducted and reported? By default, anova = FALSE, but when there are more than two levels in the independent variable, the value will change such tat anova = TRUE.
• round_f: number of decimal places to which to round the f statistic (default = 2)
• round_t: number of decimal places to which to round the t statistic (default = 2)
• round_t_test_df: number of decimal places to which to round the degrees of freedom for t tests (default = 2)

Returns

the output will be a data.table showing results of all pairwise comparisons between levels of the independent variable.

Examples

## Not run:

# Basic example
t_test_pairwise(
data = iris, iv_name = "Species", dv_name = "Sepal.Length")
# Welch's t-test
t_test_pairwise(
data = mtcars, iv_name = "am", dv_name = "hp")
# A Student's t-test
t_test_pairwise(
data = mtcars, iv_name = "am", dv_name = "hp", welch = FALSE)
# Other examples
t_test_pairwise(data = iris, iv_name = "Species",
dv_name = "Sepal.Length", t_test_stats = TRUE, sd = TRUE)
t_test_pairwise(
data = iris, iv_name = "Species", dv_name = "Sepal.Length",
mann_whitney = FALSE)
## End(Not run)