robincar_logrank {RobinCar} | R Documentation |
Robust (potentially stratified) logrank adjustment
Description
Perform a robust covariate-adjusted logrank test ("CL") that can be stratified ("CSL") if desired.
Usage
robincar_logrank(adj_method, ...)
Arguments
adj_method |
Adjustment method, one of "CL", "CSL" |
... |
Additional arguments to 'robincar_tte' |
Value
A result object with the following attributes:
result |
A list: "statistic" is the adjusted logrank test statistic which can be used to obtain p-values; "U" and "se" are the numerator and denominator of the test statistic, respectively. |
settings |
The covariate adjustment settings used. |
original_df |
The dataset supplied by the user. |
Examples
library(magrittr)
library(dplyr)
library(forcats)
set.seed(0)
n=100
data.simu0=data_gen(n=n,
theta=0,
randomization="permuted_block",
p_trt=0.5,
case="case2") %>% mutate(strata1=sample(letters[1:3],n,replace=TRUE),
strata2=sample(LETTERS[4:5],n,replace=TRUE))
out <- robincar_logrank(df=data.simu0,
treat_col="I1",
p_trt=0.5,
ref_arm=0,
response_col="t",
event_col="delta",
covariate_cols=c("model_z1", "model_z2"),
car_scheme="simple",
adj_method=c("CL"))
set.seed(0)
n=100
data.simu0=data_gen(n=n,
theta=0,
randomization="permuted_block",
p_trt=0.5,
case="case1")
data.simu <- data.simu0 %>%
tidyr::pivot_longer(cols=starts_with("car_strata"),
names_prefix="car_strata",
names_to="strt") %>%
filter(value==1) %>% select(-value) %>%
mutate(strt=forcats::as_factor(strt)) %>%
select(t,strt) %>%
left_join(data.simu0, .)
out1 <- robincar_logrank(df=data.simu,
treat_col="I1",
p_trt=0.5,
ref_arm=0,
response_col="t",
event_col="delta",
car_strata_cols="strt",
covariate_cols=NULL,
car_scheme=c("permuted-block"),
adj_method=c("CSL")
)
[Package RobinCar version 0.3.0 Index]