Fit a standard (unweighted) Cox proportional hazards model

Convenience wrapper around survival::coxph() using counting-process (tstart, tstop) time variables. Returns log-hazard ratio estimates with standard errors and the hazard ratio with 95% confidence intervals.

Usage

get_cox_fit_se(data, covariate = "x")

Arguments

data

A data frame in long (counting-process) format containing columns tstart, tstop, delta, and the covariate named by covariate.

covariate

Character string. Name of the predictor covariate column. Default is "x".

Value

A data frame with one row per term containing:

term

Covariate name.

log_hr

Log hazard ratio estimate.

log_hr_se

Standard error of the log hazard ratio.

hr

Hazard ratio estimate.

hr_ci_low

Lower 95% confidence limit.

hr_ci_high

Upper 95% confidence limit.

Examples

set.seed(20240429)
dat <- sim_data_se(n = 500)
dat_long <- get_ipcw_wgt_se(dat)
get_cox_fit_se(dat_long)
#> # A tibble: 1 × 6
#>   term  log_hr log_hr_se    hr hr_ci_low hr_ci_high
#>   <chr>  <dbl>     <dbl> <dbl>     <dbl>      <dbl>
#> 1 x      -1.85     0.147 0.157     0.117      0.209