Skip to contents

Log-Rank Score Functions for Survival Analysis

Source: R/survival_score.R
survival_score_functions.Rd

These functions compute the log-rank score statistics for a survival analysis. Depending on the function, these are stratified and/or adjusted for covariates.

Usage 

h_lr_score_no_strata_no_cov(
  theta,
  df,
  treatment,
  time,
  status,
  n = nrow(df),
  use_ties_factor = TRUE,
  calculate_variance = TRUE
)

h_lr_score_strat(
  theta,
  df,
  treatment,
  time,
  status,
  strata,
  use_ties_factor = TRUE,
  calculate_variance = TRUE
)

h_lr_score_cov(
  theta,
  df,
  treatment,
  time,
  status,
  model,
  theta_hat = theta,
  use_ties_factor = TRUE,
  hr_se_plugin_adjusted = TRUE,
  calculate_variance = TRUE
)

h_lr_score_strat_cov(
  theta,
  df,
  treatment,
  time,
  status,
  strata,
  model,
  theta_hat = theta,
  use_ties_factor = TRUE,
  hr_se_plugin_adjusted = TRUE,
  calculate_variance = TRUE
)

Arguments

theta

(number) The assumed log hazard ratio of the second vs. the first level of the treatment arm variable.

df

(data.frame) The data frame containing the survival data.

treatment

(string) The name of the treatment arm variable in df. It should be a factor with two levels, where the first level is the reference group.

time

(string) The name of the time variable in df, representing the survival time.

status

(string) The name of the status variable in df, with 0 for censored and 1 for event.

n

(count) The number of observations. Note that this can be higher than the number of rows when used in stratified analyses computations.

use_ties_factor

(flag) Whether to use the ties factor in the variance calculation. This is used when calculating the score test statistic, but not when estimating the log hazard ratio.

calculate_variance

(flag) Whether to calculate the variance. This is useful to avoid unnecessary computations when only the score function value is needed, e.g., during root finding.

strata

(character) The names of the strata variables in df, which must be factors.

model

(formula) The model formula for covariate adjustment, e.g., ~ cov1 + cov2.

theta_hat

(number) The estimated log hazard ratio when not adjusting for covariates.

hr_se_plugin_adjusted

(flag) Defines the method for calculating the standard error of the log hazard ratio estimate when adjusting for covariates, see details.

Value

The score function value(s), with the following attributes:

  • sigma_l2: The variance of the log-rank statistic.

  • se_theta_l: The corresponding standard error term for the log hazard ratio.

  • n: The number of observations used in the calculation.

Details

  • The hr_se_plugin_adjusted flag is relevant only for the standard error of the covariate adjusted log hazard ratio estimate: When TRUE, the adjusted hazard ratio estimate is plugged in into the variance formula, as per the original publication. On the other hand, when FALSE, the unadjusted estimate is used instead. This is explained in more detail in the vignette "Survival Analysis with RobinCar2" in Section "Covariate adjusted analysis without strata".

  • Note that for the not covariate adjusted score functions, these also work with a numeric theta vector of length > 1.

Functions

  • h_lr_score_no_strata_no_cov(): without strata or covariates.

  • h_lr_score_strat(): with strata but without covariates.

  • h_lr_score_cov(): with covariates but without strata.

  • h_lr_score_strat_cov(): with strata and covariates.