estimate_mdiff_paired: Estimate magnitude of difference between two related...

In rcalinjageman/esci4: Effect Sizes and Confidence Intervals

Estimate magnitude of difference between two related measures.

Description

\loadmathjax

estimate_mdiff_paired returns effect sizes estimating the magnitude of difference between two related quantiative measures.

Usage

estimate_mdiff_paired(
  data = NULL,
  comparison_measure = NULL,
  reference_measure = NULL,
  comparison_mean = NULL,
  comparison_sd = NULL,
  reference_mean = NULL,
  reference_sd = NULL,
  n = NULL,
  correlation = NULL,
  comparison_measure_name = "Comparison measure",
  reference_measure_name = "Reference measure",
  conf_level = 0.95,
  save_raw_data = TRUE
)

Arguments

data	For raw data - a dataframe or tibble
comparison_measure	For raw data - The column name of comparison measure of the outcome variable, or a vector of numeric data
reference_measure	For raw data - The column name of the reference measure of the outcome variable, or a vector of numeric data
comparison_mean	For summary data, a numeric
comparison_sd	For summary data, numeric > 0
reference_mean	For summary data, a numeric
reference_sd	For summary data, numeric > 0
n	For summary data, a numeric integer > 0
correlation	For summary data, correlation between measures, numeric > -1 and < 1
comparison_measure_name	For summary data - An optional character label for the comparison measure. Defaults to 'Comparison measure'
reference_measure_name	For summary data - An optional character label for the reference measure. Defaults to 'Reference measure'
conf_level	The confidence level for the confidence interval. Given in decimal form. Defaults to 0.95.
save_raw_data	For raw data; defaults to TRUE; set to FALSE to save memory by not returning raw data in estimate object

Value

Returns object of class esci_estimate

Examples

# From Raw Data ------------------------------------
# Just pass in the data source, grouping column, and outcome column.
# You can pass these in by position, skipping the labels:

# Note... not sure if PlantGrowth dataset meets assumptions for this analysis
estimate_mdiff_paired(
 datasets::iris,
 Sepal.Length,
 Petal.Length
)

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