compare2numvars: Comparison for columns of numbers for 2 groups

In wrappedtools: Useful Wrappers Around Commonly Used Functions

Comparison for columns of numbers for 2 groups

Description

compare2numvars computes either t_var_test or wilcox.test, depending on parameter gaussian. Descriptive statistics, depending on distribution, are reported as well.

Usage

compare2numvars(
  data,
  dep_vars,
  indep_var,
  gaussian,
  round_p = 3,
  round_desc = 2,
  range = FALSE,
  rangesep = " ",
  pretext = FALSE,
  mark = FALSE,
  n = FALSE,
  add_n = FALSE,
  singleline = TRUE,
  indentor = "     ",
  ci = FALSE,
  n_boot = 10^4
)

Arguments

data	name of dataset (tibble/data.frame) to analyze.
dep_vars	vector of column names for independent variables.
indep_var	name of grouping variable, has to translate to 2 groups. If more levels are encountered, an error is produced.
gaussian	logical specifying normal or ordinal values.
round_p	level for rounding p-value.
round_desc	number of significant digits for rounding of descriptive stats.
range	include min/max?
rangesep	text between statistics and range or other elements.
pretext	for function formatP.
mark	for function formatP.
n	create columns for n per group?
add_n	add n to descriptive statistics. Will automatically be set to TRUE, if singleline = FALSE and n = TRUE to keep it for the long table format.
singleline	Put all group levels in a single line (default) or below each other.
indentor	Optional text element to indent descriptivestats when using singleline = FALSE. Defaults to " ".
ci	Computes lower and upper confidence limits for the estimated mean/median, based on bootstrapping.
n_boot	Number of bootstrap samples for confidence limits.

Value

A tibble with variable names, descriptive statistics, and p-value, number of rows is number of dep_vars.

Examples

# Assuming Normal distribution:
compare2numvars(
  data = mtcars, dep_vars = c("wt", "mpg", "qsec"), indep_var = "am",
  gaussian = TRUE
)
compare2numvars(
  data = mtcars, dep_vars = c("wt", "mpg", "qsec"), indep_var = "am",
  gaussian = TRUE, singleline = FALSE
)
# Ordinal scale:
compare2numvars(
  data = mtcars, dep_vars = c("wt", "mpg", "qsec"), indep_var = "am",
  gaussian = FALSE, add_n = TRUE, range = TRUE
)
# If dependent variable has more than 2 levels, consider fct_lump:
mtcars |> dplyr::mutate(gear=factor(gear) |> forcats::fct_lump_n(n=1)) |> 
compare2numvars(dep_vars="wt",indep_var="gear",gaussian=TRUE)

wrappedtools documentation built on June 8, 2025, 10:58 a.m.