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
p̂
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
p̂
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
p̂
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
p̂
Standard
Error
z
p.value
14
0
32
0.438
0.0866
0.433
0.665