G-computation Maximum Likelihood Bootstrap — calc_gcomp

Computes the mean difference in treatment effects using bootstrap resampling.

Usage

calc_gcomp_ml(strategy, analysis_params)

Arguments

strategy

A list specifying the model strategy, including:

R: Number of bootstrap replications.
formula: A linear regression formula object.
family: A family object specifying the distribution and link function (e.g., binomial).
N: Synthetic sample size for g-computation.

ipd

Individual patient data.

ald

Aggregate-level data.

Value

A list containing:

mean_A: Bootstrap estimates for comparator treatment group "A".
mean_C: Bootstrap estimates for reference treatment group "C".

Examples

if (FALSE) { # \dontrun{
strategy <- list(
  R = 1000,
  formula = y ~ trt + age,
  family = binomial(),
  trt_var = "treatment",
  N = 1000
)
ipd <- data.frame(trt = c("A", "C"),
                  y = c(1, 0),
                  age = c(30, 40))
ald <- data.frame()
calc_gcomp_ml(strategy, ipd, ald)
} # }