Add p-value

Calculate and add a p-value comparing the two variables in the cross table. If missing levels are included in the tables, they are also included in p-value calculation.

# S3 method for class 'tbl_cross'
add_p(
  x,
  test = NULL,
  pvalue_fun = ifelse(source_note, label_style_pvalue(digits = 1, prepend_p = TRUE),
    label_style_pvalue(digits = 1)),
  source_note = FALSE,
  test.args = NULL,
  ...
)

Arguments

x

(tbl_cross)
Object with class tbl_cross created with the tbl_cross() function

test

(string)
A string specifying statistical test to perform. Default is "chisq.test" when expected cell counts >=5 and "fisher.test" when expected cell counts <5.

pvalue_fun

(function)
Function to round and format p-value. Default is label_style_pvalue(digits = 1), except when source_note = TRUE when the default is label_style_pvalue(digits = 1, prepend_p = TRUE)

source_note

(scalar logical)
Logical value indicating whether to show p-value in the {gt} table source notes rather than a column.

test.args

(named list)
Named list containing additional arguments to pass to the test (if it accepts additional arguments). For example, add an argument for a chi-squared test with test.args = list(correct = TRUE)

...

These dots are for future extensions and must be empty.

Author

Karissa Whiting, Daniel D. Sjoberg

Examples

# Example 1 ----------------------------------
trial |>
  tbl_cross(row = stage, col = trt) |>
  add_p()


  

      

        
Chemotherapy Treatment
      
      
Total
      
p-value1
    
Drug A
      
Drug B
    
T Stage






0.9
    T1
28
25
53

    T2
25
29
54

    T3
22
21
43

    T4
23
27
50

Total
98
102
200

1 Pearson’s Chi-squared test
    

# Example 2 ----------------------------------
trial |>
  tbl_cross(row = stage, col = trt) |>
  add_p(source_note = TRUE)


  

      

        
Chemotherapy Treatment
      
      
Total
    
Drug A
      
Drug B
    
T Stage





    T1
28
25
53
    T2
25
29
54
    T3
22
21
43
    T4
23
27
50
Total
98
102
200
Pearson’s Chi-squared test, p=0.9