estimate_pdiff_one: Estimate magnitudes of difference from a single measure...

In rcalinjageman/esci4: Effect Sizes and Confidence Intervals

Estimate magnitudes of difference from a single measure compared to a know reference.

Description

Returns effect sizes appropriate for designs with one quantitative variable compared against a known reference.

Usage

estimate_pdiff_one(
  data = NULL,
  outcome_variable = NULL,
  comparison_cases = NULL,
  comparison_n = NULL,
  reference_p = 0,
  case_label = 1,
  outcome_variable_name = "My outcome variable",
  conf_level = 0.95,
  count_NA = FALSE
)

Arguments

data	For raw data - a dataframe or tibble
outcome_variable	For raw data - The column name of the outcome variable, which must be a factor, or a vector that is a factor
comparison_cases	For summary data, a numeric integer > 0
comparison_n	For summary data, a numeric integer >= count
reference_p	Reference proportion, numeric >=0 and <=1
case_label	An optional numeric or character label for the count level.
outcome_variable_name	Optional friendly name for the outcome variable. Defaults to 'My outcome variable' or the outcome variable column name if a data frame is passed.
conf_level	The confidence level for the confidence interval. Given in decimal form. Defaults to 0.95.
count_NA	Logical to count NAs (TRUE) in total N or not (FALSE)

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_pdiff_one(
 datasets::PlantGrowth,
 group,
 reference_p = 0.33
)

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