Usage
h_tbl_coxph_pairwise(df, variables, control_coxph_pw = control_coxph())Arguments
- df
(
data.frame)
data set containing all analysis variables.- variables
-
(named
list)
variable names. Details are:tte(numeric)
variable indicating time-to-event duration values.is_event(logical)
event variable.TRUEif event,FALSEif time to event is censored.arm(factor)
the treatment group variable.strat(characterorNULL)
variable names indicating stratification factors.
- control_coxph_pw
-
(
list)
parameters for comparison details, specified by using the helper functioncontrol_coxph(). Some possible parameter options are:pval_method(string)
p-value method for testing hazard ratio = 1. Default method is"log-rank", can also be set to"wald"or"likelihood".ties(string)
method for tie handling. Default is"efron", can also be set to"breslow"or"exact". See more insurvival::coxph()conf_level(proportion)
confidence level of the interval for HR.
Value
A data.frame containing statistics HR, XX% CI (XX taken from control_coxph_pw),
and p-value (log-rank).
Examples
# \donttest{
library(dplyr)
adtte <- tern_ex_adtte %>%
filter(PARAMCD == "OS") %>%
mutate(is_event = CNSR == 0)
h_tbl_coxph_pairwise(
df = adtte,
variables = list(tte = "AVAL", is_event = "is_event", arm = "ARM"),
control_coxph_pw = control_coxph(conf_level = 0.9)
)
#> HR 90% CI p-value (log-rank)
#> B: Placebo 1.41 (1.01, 1.96) 0.0905
#> C: Combination 1.81 (1.24, 2.64) 0.0086
# }