stats_by_group: Compute Statistics by Group

In rettopnivek/arfpam: Assorted R Functions for Processing, Analysis, and Modeling

Compute Statistics by Group

Description

A function to compute assorted univariate statistics for a specified variable in a data frame over desired grouping factors.

Usage

stats_by_group(
  dtf,
  column,
  groupings,
  statistics = c("M", "SD"),
  method = "Student's T",
  categories = 1,
  width = 0.95,
  na.rm = TRUE
)

Arguments

dtf	A data frame.
column	A character string, the column in dtf to compute statistics for.
groupings	A character vector, the columns in dtf to use as grouping factors (it is recommended that they all be categorical variables).
statistics	A character vector, the set of different statistics to compute over groups.
method	A character string, the type of method to use when computing uncertainty intervals. Options include: "Student's T" for means or "Beta-binomial" for proportions.
categories	An optional vector of elements to match over when computing frequencies, proportions, or percentages.
width	A numeric value between 0 and 1, the width for uncertainty intervals.
na.rm	A logical value; if TRUE removes NA values.

Details

Possible univariate statistics that can be computed:

• 'N' = Sample size;

• 'M' = Mean;

• 'Md' = Median;

• 'SD' = Standard deviation;

• 'SE' = Standard error of the mean;

• 'C' = Counts/frequencies;

• 'Pr' = Proportions;

• 'P' = Percentages.

Additionally, specifying 'UI' in combination with the argument method will compute the lower and upper limits of a desired uncertainty interval. The width of the interval can be controlled by the argument width.

Value

A data frame with separate rows for each combination of grouping factors and separate columns for each statistic to compute.

Examples

# Example data set
data(iris)
dtf <- iris

# Mean/SD for sepal length by species
dtf |> stats_by_group( 'Sepal.Length', 'Species' )

# Create additional categorical variable
dtf$Long_petal <- c( 'No', 'Yes' )[
  ( dtf$Petal.Length > median( dtf$Petal.Length) ) + 1
]
# Sample size, mean, and confidence intervals using Student's T
# distribution by species and whether petals are long
dtf |> stats_by_group(
  'Sepal.Length', c( 'Species', 'Long_petal' ), c( 'N', 'M', 'UI' )
)

# Create additional categorical variable
dtf$Long_sepal <- c( 'No', 'Yes' )[
  ( dtf$Sepal.Length > median( dtf$Sepal.Length) ) + 1
]
# Proportion and confidence intervals based on beta-binomial
# distribution for long sepals by long petals
dtf |> stats_by_group(
  'Long_sepal', c( 'Long_petal' ), c( 'N', 'Pr', 'UI' ),
  categories = 'Yes', method = 'Beta-binomial'
)

rettopnivek/arfpam documentation built on Oct. 20, 2024, 7:24 p.m.