overview: Calculates descriptive statistics for a numerical variable

In rcalinjageman/esci4: Effect Sizes and Confidence Intervals

Calculates descriptive statistics for a numerical variable

Description

This function caluclated basic descriptive statistics for a numerical variable. It can calculate an overall summary, or broken down by the levels of a grouping variable. Inputs can be summary data, vectors, or a data frame.

Usage

overview(
  data = NULL,
  outcome_variable = NULL,
  grouping_variable = NULL,
  means = NULL,
  sds = NULL,
  ns = NULL,
  grouping_variable_levels = NULL,
  outcome_variable_name = "My Outcome Variable",
  grouping_variable_name = NULL,
  conf_level = 0.95,
  assume_equal_variance = FALSE
)

Arguments

data	for raw data, a data frame or tibble
outcome_variable	for raw data, either a vector containing numerical data or the name of a data-frame column containing a factor
grouping_variable	optional; for raw data either a vector containing a factor or the name of a data frame column containing a factor
means	For summary data - A vector of 1 or more numerical means
sds	For summary data - A vector of standard deviations, same length as means
ns	For summary data - A vector of sample sizes, same length as means
grouping_variable_levels	For summary data - An optional vector of group labels, same length as means. If not passed, auto-generated.
outcome_variable_name	Optional friendly name for the outcome variable. Defaults to 'My Outcome Variable'. Ignored if a data-frame is passed, this argument is ignored.
grouping_variable_name	Optional friendly name for the grouping variable. If a data frame is passed, this argument is ignored.
conf_level	The confidence level for the confidence interval. Given in decimal form. Defaults to 0.95.
assume_equal_variance	Defaults to FALSE

Value

Returns a table of descriptive statistics

Examples

# From Summary data --------------------------------------

overview(
  means = c(37.5, 31.9, 41.2, 33.4, 29.9, 38.3),
  sds = c(10, 13.5, 14.8, 10, 8.7, 10),
  ns = c(19, 19, 19, 19, 19, 19),
  grouping_variable_levels = c(
     "NFree10", "AFree10", "ADiet10", "NFree17", "AFree17", "ADiety17"
  ),
  outcome_variable_name = "% time near target",
  grouping_variable_name = "Diet",
  assume_equal_variance = TRUE
)

rcalinjageman/esci4 documentation built on May 18, 2023, 4:01 a.m.