wakefield (version 0.3.6)

sex_inclusive: Generate Random Vector of Non-Binary Genders

Description

Generate a random vector of non-binary genders. Proportion of trans* category was taken from the Williams Institute Report (2011), and subtracted equally from the male and female categories.

Usage

sex_inclusive(
  n,
  x = c("Male", "Female", "Intersex"),
  prob = NULL,
  name = "Sex"
)
gender_inclusive(
  n,
  x = c("Male", "Female", "Trans*"),
  prob = NULL,
  name = "Gender"
)

Arguments

n

The number elements to generate. This can be globally set within the environment of r_data_frame or r_list.

x

A vector of elements to chose from.

prob

A vector of probabilities to chose from.

name

The name to assign to the output vector's varname attribute. This is used to auto assign names to the column/vector name when used inside of r_data_frame or r_list.

Value

Returns a random factor vector of sex or gender elements.

Details

The genders and probabilities used match approximate gender make-up:

Gender	Percent
Male	51.07 %
Female	48.63 %
Trans*	0.30 %

See Also

Other variable functions: age(), animal(), answer(), area(), car(), children(), coin(), color, date_stamp(), death(), dice(), dna(), dob(), dummy(), education(), employment(), eye(), grade_level(), grade(), group(), hair(), height(), income(), internet_browser(), iq(), language, level(), likert(), lorem_ipsum(), marital(), military(), month(), name, normal(), political(), race(), religion(), sat(), sentence(), sex(), smokes(), speed(), state(), string(), upper(), valid(), year(), zip_code()

Examples

# NOT RUN {
sex_inclusive(10)
barplot(table(sex_inclusive(10000)))

gender_inclusive(10)
barplot(table(gender_inclusive(10000)))
# }