sex_inclusive: Generate Random Vector of Non-Binary Genders
In wakefield: Generate Random Data Sets

Description Usage Arguments Details Value Author(s) See Also Examples

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.

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

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

`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`.

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

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

Returns a random factor vector of sex or gender elements.

Matthew Sigal <msigal@yorku.ca>

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()

sex_inclusive(10)
barplot(table(sex_inclusive(10000)))

gender_inclusive(10)
barplot(table(gender_inclusive(10000)))

 [1] Female   Female   Male     Female   Female   Male     Male     Female  
 [9] Intersex Female  
Levels: Male Female Intersex
 [1] Female Male   Trans* Male   Female Female Trans* Female Trans* Trans*
Levels: Male Female Trans*