A tidier version of prop.test() for equal or given proportions.
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,
...
)
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 |
explanatory | The variable name in |
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 |
alternative | Character string giving the direction of the alternative
hypothesis. Options are |
conf_int | A logical value for whether to report the confidence
interval or not. |
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 |
correct | A logical indicating whether Yates' continuity correction
should be applied where possible. If |
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 |
... | Additional arguments for prop.test(). |
Other wrapper functions:
chisq_stat()
,
chisq_test()
,
observe()
,
t_stat()
,
t_test()
# two-sample proportion test for difference in proportions of
# college completion by respondent sex
prop_test(gss,
college ~ sex,
order = c("female", "male"))
#> # A tibble: 1 × 6
#> statistic chisq_df p_value alternative lower_ci upper_ci
#> <dbl> <dbl> <dbl> <chr> <dbl> <dbl>
#> 1 0.0000204 1 0.996 two.sided -0.101 0.0917
# one-sample proportion test for hypothesized null
# proportion of college completion of .2
prop_test(gss,
college ~ NULL,
p = .2)
#> # A tibble: 1 × 4
#> statistic chisq_df p_value alternative
#> <dbl> <int> <dbl> <chr>
#> 1 636. 1 2.98e-140 two.sided
# 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)
#> # A tibble: 1 × 3
#> statistic p_value alternative
#> <dbl> <dbl> <chr>
#> 1 8.27 1.30e-16 two.sided