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Add p-value

Source: R/add_p.tbl_survfit.R
add_p.tbl_survfit.Rd

Calculate and add a p-value to stratified tbl_survfit() tables.

Usage

# S3 method for class 'tbl_survfit'
add_p(
  x,
  test = "logrank",
  test.args = NULL,
  pvalue_fun = label_style_pvalue(digits = 1),
  include = everything(),
  quiet,
  ...
)

Arguments

x

(tbl_survfit)
Object of class "tbl_survfit"

test

(string)
string indicating test to use. Must be one of "logrank", "tarone", "survdiff", "petopeto_gehanwilcoxon", "coxph_lrt", "coxph_wald", "coxph_score". See details below

test.args

(named list)
named list of arguments that will be passed to the method specified in the test argument. Default is NULL.

pvalue_fun

(function)
Function to round and format p-values. Default is label_style_pvalue(). The function must have a numeric vector input, and return a string that is the rounded/formatted p-value (e.g. pvalue_fun = label_style_pvalue(digits = 2)).

include

(tidy-select)
Variables to include in output. Default is everything().

quiet

[Deprecated]

...

These dots are for future extensions and must be empty.

test argument

The most common way to specify test= is by using a single string indicating the test name. However, if you need to specify different tests within the same table, the input in flexible using the list notation common throughout the gtsummary package. For example, the following code would call the log-rank test, and a second test of the G-rho family.

... |>
  add_p(test = list(trt ~ "logrank", grade ~ "survdiff"),
        test.args = grade ~ list(rho = 0.5))

Note

To calculate the p-values, the formula is re-constructed from the the call in the original survfit() object. When the survfit() object is created a for loop, lapply(), purrr::map() setting the call may not reflect the true formula which may result in an error or an incorrect calculation.

To ensure correct results, the call formula in survfit() must represent the formula that will be used in survival::survdiff(). If you utilize the tbl_survfit.data.frame() S3 method, this is handled for you.

See also

Other tbl_survfit tools: add_nevent.tbl_survfit()

Examples

library(survival)

gts_survfit <-
  list(
    survfit(Surv(ttdeath, death) ~ grade, trial),
    survfit(Surv(ttdeath, death) ~ trt, trial)
  ) |>
  tbl_survfit(times = c(12, 24))

# Example 1 ----------------------------------
gts_survfit |>
  add_p()



  
Characteristic
      Time 12
      Time 24
      p-value1
    
Grade




0.072
    I
97% (93%, 100%)
51% (41%, 65%)

    II
82% (74%, 92%)
47% (37%, 61%)

    III
86% (78%, 95%)
33% (23%, 47%)

Chemotherapy Treatment




0.2
    Drug A
91% (85%, 97%)
47% (38%, 58%)

    Drug B
86% (80%, 93%)
41% (33%, 52%)

1 Log-rank test
    

# Example 2 ----------------------------------
# Pass `rho=` argument to `survdiff()`
gts_survfit |>
  add_p(test = "survdiff", test.args = list(rho = 0.5))



  
Characteristic
      Time 12
      Time 24
      p-value1
    
Grade




0.070
    I
97% (93%, 100%)
51% (41%, 65%)

    II
82% (74%, 92%)
47% (37%, 61%)

    III
86% (78%, 95%)
33% (23%, 47%)

Chemotherapy Treatment




0.2
    Drug A
91% (85%, 97%)
47% (38%, 58%)

    Drug B
86% (80%, 93%)
41% (33%, 52%)

1 G-rho test (ρ = 0.5)