Compute Summary Statistics

This function calculates summary statistics for a given numeric vector, including mean, standard deviation, quartiles, and missing value counts. The function supports both population and sample standard deviation calculations.

Usage

summary_stat(x, descriptive = FALSE)

Arguments

x

A numeric vector containing the sample data.

descriptive

A logical value indicating whether to use the descriptive (population) standard deviation (TRUE) or the sample standard deviation (FALSE, default).

Value

A data frame with the following columns:

mean

The mean of the non-missing values in x.

sd

The standard deviation of the non-missing values in x.

q25

The 25th percentile (first quartile).

q50

The 50th percentile (median).

q75

The 75th percentile (third quartile).

n_val

The count of non-missing values.

n_na

The count of missing values.

Examples

# Generate example data
set.seed(123)
data <- c(rnorm(100, mean = 50, sd = 10), NA, NA)

# Compute summary statistics
summary_stat(data)
#>       mean       sd      min      q25      q50      q75      max n_val n_na
#> 1 50.90406 9.128159 26.90831 45.06146 50.61756 56.91819 71.87333   100    2
summary_stat(data, descriptive = TRUE)
#>       mean       sd      min      q25      q50      q75      max n_val n_na
#> 1 50.90406 9.082403 26.90831 45.06146 50.61756 56.91819 71.87333   100    2