Covariate adjustment for time to event data

Perform a covariate-adjusted logrank test (`adj_method="CL"`), covariate-adjusted stratified logrank test (`adj_method="CSL"`), or a covariate-adjusted robust Cox score test (`adj_method="coxscore"`).

robincar_tte(
  df,
  treat_col,
  response_col,
  event_col,
  adj_method,
  car_strata_cols = NULL,
  covariate_cols = NULL,
  p_trt = 0.5,
  ref_arm = NULL,
  sparse_remove = TRUE,
  car_scheme = "simple"
)

Arguments

df

A data.frame with the required columns

treat_col

Name of column in df with treatment variable

response_col

Name of the column in df with response variable

event_col

Name of column in df with event indicator (0/FALSE=no event, 1/TRUE=event)

adj_method

Adjustment method (one of "CL", "CSL", or "coxscore")

car_strata_cols

Names of columns in df with car_strata variables

covariate_cols

Names of columns in df with covariate variables

p_trt

Treatment allocation ratio for the reference arm.

ref_arm

Reference arm of the treatment group, defaults to NULL, which results in using the first element of `unique(data[, treat_col])`.

sparse_remove

Remove sparse car_strata from calculation

car_scheme

Name of the type of covariate-adaptive randomization scheme. One of: "simple", "pocock-simon", "biased-coin", "permuted-block".

Value

For adjustment method "CL" or "CSL", see value of RobinCar::robincar_logrank(); for adjustment method "coxscore" see value of RobinCar::robincar_coxscore().

Details

`robincar_coxscore` and `robincar_logrank` are wrapper functions around `robincar_tte`.