Add multiple comparison adjustment

Adjustments to p-values are performed with stats::p.adjust().

add_q(x, method = "fdr", pvalue_fun = NULL, quiet = NULL)

Arguments

x

(gtsummary)
a gtsummary object with a column named "p.value"

method

(string)
String indicating method to be used for p-value adjustment. Methods from stats::p.adjust() are accepted. Default is method='fdr'. Must be one of 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none'

pvalue_fun

(function)
Function to round and format q-values. Default is the function specified to round the existing 'p.value' column.

quiet

Author

Daniel D. Sjoberg, Esther Drill

Examples

# Example 1 ----------------------------------
add_q_ex1 <-
  trial |>
  tbl_summary(by = trt, include = c(trt, age, grade, response)) |>
  add_p() |>
  add_q()

# Example 2 ----------------------------------
trial |>
  tbl_uvregression(
    y = response,
    include = c("trt", "age", "grade"),
    method = glm,
    method.args = list(family = binomial),
    exponentiate = TRUE
  ) |>
  add_global_p() |>
  add_q()


  
Characteristic
      
N
      
OR
      
95% CI
      
p-value
      
q-value1
    
Chemotherapy Treatment
193




0.5
0.8
    Drug A


—
—



    Drug B


1.21
0.66, 2.24



Age
183
1.02
1.00, 1.04
0.091
0.3
Grade
193




>0.9
>0.9
    I


—
—



    II


0.95
0.45, 2.00



    III


1.10
0.52, 2.29



Abbreviations: CI = Confidence Interval, OR = Odds Ratio
    
1 False discovery rate correction for multiple testing