Learn R Programming

survminer (version 0.4.9)

pairwise_survdiff: Multiple Comparisons of Survival Curves

Description

Calculate pairwise comparisons between group levels with corrections for multiple testing.

Usage

pairwise_survdiff(formula, data, p.adjust.method = "BH", na.action, rho = 0)

Arguments

formula

a formula expression as for other survival models, of the form Surv(time, status) ~ predictors.

data

a data frame in which to interpret the variables occurring in the formula.

p.adjust.method

method for adjusting p values (see p.adjust). Allowed values include "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none". If you don't want to adjust the p value (not recommended), use p.adjust.method = "none".

na.action

a missing-data filter function. Default is options()$na.action.

rho

a scalar parameter that controls the type of test. Allowed values include 0 (for Log-Rank test) and 1 (for peto & peto test).

Value

Returns an object of class "pairwise.htest", which is a list containing the p values.

See Also

survival::survdiff

Examples

Run this code
# NOT RUN {
library(survival)
library(survminer)
data(myeloma)

# Pairwise survdiff
res <- pairwise_survdiff(Surv(time, event) ~ molecular_group,
     data = myeloma)
res

# Symbolic number coding
symnum(res$p.value, cutpoints = c(0, 0.0001, 0.001, 0.01, 0.05, 0.1, 1),
   symbols = c("****", "***", "**", "*", "+", " "),
   abbr.colnames = FALSE, na = "")


# }

Run the code above in your browser using DataLab