Covariate-adjusted estimators for time to event data

Estimate a covariate-adjusted hazard ratio (`adj_method="CL"`), or a covariate-adjusted stratified hazard ratio (`adj_method="CSL"`).

robincar_covhr(
  df,
  treat_col,
  response_col,
  event_col,
  car_strata_cols = NULL,
  covariate_cols = NULL,
  p_trt = 0.5,
  ref_arm = NULL,
  car_scheme = "simple",
  adj_method = "CL",
  interval = c(-10, 10)
)

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)
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])`.
car_scheme: Name of the type of covariate-adaptive randomization scheme. One of: "simple", "pocock-simon", "biased-coin", "permuted-block".
adj_method: Adjustment method (one of "CL", "CSL")
interval: Interval for uniroot function

Value

An object with attribute named "result", which lists:

theta_L: estimate of the hazard ratio
se_theta_L: SE estimate of the hazard ratio
theta_CL: estimate of the covariate-adjusted hazard ratio
se_theta_CL: SE estimate of the covariate-adjusted hazard ratio

Other attributes are the settings used, data attributes, and the original data frame supplied by the user.