infer: prop_test – R documentation

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infer

prop_test

Tidy proportion test

Description

A tidier version of prop.test() for equal or given proportions.

Usage

prop_test(
  x,
  formula,
  response = NULL,
  explanatory = NULL,
  p = NULL,
  order = NULL,
  alternative = "two-sided",
  conf_int = TRUE,
  conf_level = 0.95,
  success = NULL,
  correct = NULL,
  z = FALSE,
  ...
)

Arguments

`x`	A data frame that can be coerced into a tibble.
`formula`	A formula with the response variable on the left and the explanatory on the right, where an explanatory variable NULL indicates a test of a single proportion.
`response`	The variable name in `x` that will serve as the response. This is alternative to using the `formula` argument. This is an alternative to the formula interface.
`explanatory`	The variable name in `x` that will serve as the explanatory variable. Optional. This is an alternative to the formula interface.
`p`	A numeric vector giving the hypothesized null proportion of success for each group.
`order`	A string vector specifying the order in which the proportions should be subtracted, where `order = c("first", "second")` means `"first" - "second"`. Ignored for one-sample tests, and optional for two sample tests.
`alternative`	Character string giving the direction of the alternative hypothesis. Options are `"two-sided"` (default), `"greater"`, or `"less"`. Only used when testing the null that a single proportion equals a given value, or that two proportions are equal; ignored otherwise.
`conf_int`	A logical value for whether to report the confidence interval or not. `TRUE` by default, ignored if `p` is specified for a two-sample test. Only used when testing the null that a single proportion equals a given value, or that two proportions are equal; ignored otherwise.
`conf_level`	A numeric value between 0 and 1. Default value is 0.95. Only used when testing the null that a single proportion equals a given value, or that two proportions are equal; ignored otherwise.
`success`	The level of `response` that will be considered a success, as a string. Only used when testing the null that a single proportion equals a given value, or that two proportions are equal; ignored otherwise.
`correct`	A logical indicating whether Yates' continuity correction should be applied where possible. If `z = TRUE`, the `correct` argument will be overwritten as `FALSE`. Otherwise defaults to `correct = TRUE`.
`z`	A logical value for whether to report the statistic as a standard normal deviate or a Pearson's chi-square statistic. z^2 is distributed chi-square with 1 degree of freedom, though note that the user will likely need to turn off Yates' continuity correction by setting `correct = FALSE` to see this connection.
`...`	Additional arguments for prop.test().

Examples

# two-sample proportion test for difference in proportions of
# college completion by respondent sex
prop_test(gss,
          college ~ sex,
          order = c("female", "male"))

# one-sample proportion test for hypothesized null
# proportion of college completion of .2
prop_test(gss,
          college ~ NULL,
          p = .2)

# report as a z-statistic rather than chi-square
# and specify the success level of the response
prop_test(gss,
          college ~ NULL,
          success = "degree",
          p = .2,
          z = TRUE)

infer

Tidy Statistical Inference

v0.5.4

CC0

Authors

Andrew Bray [aut, cre], Chester Ismay [aut] (<https://orcid.org/0000-0003-2820-2547>), Evgeni Chasnovski [aut] (<https://orcid.org/0000-0002-1617-4019>), Ben Baumer [aut] (<https://orcid.org/0000-0002-3279-0516>), Mine Cetinkaya-Rundel [aut] (<https://orcid.org/0000-0001-6452-2420>), Simon Couch [ctb], Ted Laderas [ctb] (<https://orcid.org/0000-0002-6207-7068>), Nick Solomon [ctb], Johanna Hardin [ctb], Albert Y. Kim [ctb] (<https://orcid.org/0000-0001-7824-306X>), Neal Fultz [ctb], Doug Friedman [ctb], Richie Cotton [ctb] (<https://orcid.org/0000-0003-2504-802X>), Brian Fannin [ctb]

Initial release

prop_test

Description

Usage

Arguments

Examples

infer

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