All-in-one alternate two-sample means test

infer_2mean() is an alternative to infer_2mean_test() and infer_2mean_int(). Rather than have hypothesis test and confidence interval output split into two separate functions, you can now do it in one. For just a hypothesis test, do nothing different from infer_2mean_test() (except change the function name). For a confidence interval provided with that, use conf_int = "show.

Usage

infer_2mean(
  data,
  formula,
  digits = 3,
  conf_lvl = 0.95,
  conf_int = c("hide", "show"),
  caption = NULL
)

Arguments

data

A data frame (or tibble).

formula

The variables to run the test on, in formula syntax, var1 ~ var2.

digits

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

conf_lvl

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

conf_int

Should a confidence interval be provided in addition to the hypothesis test output? Defaults to "hide" with the other option being "show".

caption

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

Value

An object of class flextable. In interactive sessions, output is viewable immediately.

Examples

infer_2mean(mtcars, wt~vs)
Two Sample Independent Means Test Between wt and vs 
Confidence Level: 95%
vs
n
n
Missing
Group
Means
Standard
Error
t
df
p-value
0
18
0
3.689
0.286
3.764
29.981
0.000728
1
14
0
2.611
infer_2mean(mtcars, wt~vs, conf_lvl = .9)
Two Sample Independent Means Test Between wt and vs 
Confidence Level: 90%
vs
n
n
Missing
Group
Means
Standard
Error
t
df
p-value
0
18
0
3.689
0.286
3.764
29.981
0.000728
1
14
0
2.611
infer_2mean(mtcars, wt~vs, conf_lvl = .9, conf_int = "show")
Two Sample Independent Means Test Between wt and vs 
Confidence Level: 90%
vs
n
n
Missing
Group
Means
Standard
Error
t
df
p-value (2 tail)
90% 
Interval
Lower
90% 
Interval
Upper
0
18
0
3.689
0.286
3.764
29.981
0.000728
0.591
1.563
1
14
0
2.611