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Create a summary table for a one-sample proportion test

Usage

infer_1prop_test(
  data,
  formula,
  success = NULL,
  p0 = 0.5,
  digits = 3,
  alternative = c("notequal", "greater", "less"),
  conf_lvl = 0.95,
  caption = NULL
)

Arguments

data

A data frame (or tibble).

formula

The variable to run the test on, in formula syntax, ~var.

success

The data value that constitutes a "success".

p0

The null hypothesis value. Defaults to 0.5.

digits

The number of digits to round table values to. Defaults to 3.

alternative

The alternative hypothesis. Defaults to "notequal" (two sided p-value). Other options include "greater" or "less". Use depends on your test.

conf_lvl

The confidence level of the interval, entered as a value between 0 and 1. Defaults to 0.95.

caption

An override to the table caption. A sensible default is provided.

Value

An object of class flextable. In an interactive environment, results are viewable immediately.

Examples

infer_1prop_test(mtcars, ~vs, success = 1)
One-Sample Proportion Test on Variable vs
Successes: 1
Null Value: 0.5
p-value Reported: Two Sided

n
Successes

n
Missing

n
Used

Standard
Error

z

p.value

14

0

32

0.438

0.0884

-0.707

0.48

infer_1prop_test(mtcars, ~vs, success = 1, alternative = "less")
One-Sample Proportion Test on Variable vs
Successes: 1
Null Value: 0.5
p-value Reported: One Sided (Less Than)

n
Successes

n
Missing

n
Used

Standard
Error

z

p.value

14

0

32

0.438

0.0884

-0.707

0.24

infer_1prop_test(mtcars, ~vs, success = 1, conf_lvl = 0.90)
One-Sample Proportion Test on Variable vs
Successes: 1
Null Value: 0.5
p-value Reported: Two Sided

n
Successes

n
Missing

n
Used

Standard
Error

z

p.value

14

0

32

0.438

0.0884

-0.707

0.48

infer_1prop_test(mtcars, ~vs, success = 1, p0 = 0.4)
One-Sample Proportion Test on Variable vs
Successes: 1
Null Value: 0.4
p-value Reported: Two Sided

n
Successes

n
Missing

n
Used

Standard
Error

z

p.value

14

0

32

0.438

0.0866

0.433

0.665