mverse (version 0.2.3)

t_test_mverse: Performs one or two sample t-tests on data columns.

Description

t_test_mverse performs t-tests across the multiverse. If x or y is specified, then performs one and two sample t-tests on specified columns of the data. If both x and y are NULL, then performs t.test based on the formula branches.

Usage

t_test_mverse(
  .mverse,
  x = NULL,
  y = NULL,
  alternative = "two.sided",
  mu = 0,
  paired = FALSE,
  var.equal = FALSE,
  conf.level = 0.95,
  parallel = FALSE,
  progress = FALSE
)

Value

a multiverse table displaying the t-test results as a tibble.

Arguments

.mverse

a mverse object.

x

(optional) column name of data within mverse object

y

(optional) column name of data within mverse object

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

mu

a number indicating the true value of the mean (or difference in means if you are performing a two sample test).

paired

a logical indicating whether you want a paired t-test.

var.equal

a logical variable indicating whether to treat the two variances as being equal.

conf.level

confidence level of the interval.

parallel

passed to multiverse::execute_multiverse() to indicate whether to execute the multiverse analysis in parallel. Defaults to FALSE.

progress

passed to multiverse::execute_multiverse() to indicate whether to include a progress bar for each step of the execution. Defaults to FALSE.

Examples

# Performing a unpaired two sample t-test.
library(dplyr)
mv <- soccer %>%
  filter(!is.na(rater1), !is.na(rater2)) %>%
  mverse()
x <- mutate_branch(
  ((rater1 + rater2) / 2) > mean((rater1 + rater2) / 2),
  ifelse(rater1 > rater2, rater1 > 0.5, rater2 > 0.5)
)
y <- mutate_branch(
  redCards, yellowCards, yellowReds
)
two_sample_form <- formula_branch(y ~ x)
mv <- mv %>%
  add_mutate_branch(x, y) %>%
  add_formula_branch(two_sample_form)
t_test_mverse(mv)