Covariate Adjusted and Stratified Survival Analysis

Calculate log-rank test as well as hazard ratio estimates for survival data, optionally adjusted for covariates and a stratification factor.

Usage

robin_surv(
  formula,
  data,
  treatment,
  comparisons,
  contrast = "hazardratio",
  test = "logrank",
  ...
)

Arguments

formula: (formula) A formula of analysis, of the form Surv(time, status) ~ treatment * strata + covariates.
data: (data.frame) Input data frame.
treatment: (formula) A formula of treatment assignment or assignment by stratification.
comparisons: (list) An optional list of comparisons between treatment levels to be performed, see details. By default, all pairwise comparisons are performed automatically.
contrast: (character(1)) The contrast statistic to be used, currently only "hazardratio" is supported.
test: (character(1)) The test to be used, currently only "logrank" is supported.
...: Additional arguments passed to the survival analysis functions, in particular se_method (please see the vignette for details).

Value

A surv_effect object containing the results of the survival analysis.

Details

The user can optionally specify a list of comparisons between treatment levels to be performed. The list must have two elements:

Treatment level indices of the treatment group.
Treatment level indices of the control group.

So for example if you would like to compare level 3 with level 1, and also level 3 with level 2 (but not level 2 with level 1) then you can specify: comparisons = list(c(3, 3), c(1, 2))

Examples

robin_surv(
  formula = Surv(time, status) ~ sex * strata + meal.cal + age,
  data = surv_data,
  treatment = sex ~ strata
)
#> Model        :  Surv(time, status) ~ sex * strata + meal.cal + age 
#> Randomization:  sex ~ strata  ( Simple )
#> 
#> Contrast     :  Hazard ratio
#> 
#>                  Estimate Std.Err Z Value Pr(>|z|)   
#> Male v.s. Female  0.55219 0.19133  2.8861   0.0039 **
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> Test         :  Log-Rank
#> 
#>                  Test Stat. Pr(>|z|)   
#> Male v.s. Female     2.9496 0.003181 **
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1