Sensitivity Analysis of Hazard Ratios to k_inter — sensitivity_analysis_k

Analyzes how the interaction parameter k_inter affects hazard ratios in different populations (overall, harm subgroup, no-harm subgroup).

Usage

sensitivity_analysis_k_inter(
  k_inter_range = c(-5, 5),
  n_points = 21,
  plot = TRUE,
  ...
)

Arguments

k_inter_range: Numeric vector of length 2 specifying the range of k_inter values to analyze. Default is c(-5, 5).
n_points: Integer number of points to evaluate within the range. Default is 21.
plot: Logical indicating whether to create visualization plots. Default is TRUE.
...: Additional arguments passed to generate_aft_dgm_flex.

Value

A data.frame of class "k_inter_sensitivity" with columns:

k_inter: Numeric k_inter value
hr_harm: Numeric hazard ratio in harm subgroup
hr_no_harm: Numeric hazard ratio in no-harm subgroup
hr_overall: Numeric overall hazard ratio
subgroup_size: Integer size of harm subgroup

Details

This function evaluates the hazard ratios at evenly spaced points across the k_inter range. If plot = TRUE, it creates a 4-panel visualization showing:

Harm subgroup HR vs k_inter
All HRs (overall, harm, no-harm) vs k_inter
Ratio of HRs (harm/no-harm) showing effect modification
Table of key values

Examples

if (FALSE) { # \dontrun{
# Analyze sensitivity to k_inter
sensitivity_results <- sensitivity_analysis_k_inter(
  k_inter_range = c(-2, 2),
  n_points = 11,
  data = survival::gbsg,
  continuous_vars = c("age", "er", "pgr"),
  factor_vars = c("meno", "grade"),
  outcome_var = "rfstime",
  event_var = "status",
  treatment_var = "hormon",
  subgroup_vars = c("er", "meno"),
  subgroup_cuts = list(er = 20, meno = 0),
  model = "alt",
  plot = TRUE
)

# Results show relationship between k_inter and HRs
print(sensitivity_results)
} # }