SCM method constructor — scm • rdborrow

Creates a method object for synthetic control estimation with external control borrowing for the open-label extension phase (Zhou et al., 2024). Constructs a weighted combination of external controls matching each RCT control subject on covariates and pre-crossover outcomes. The penalty is chosen by leave-one-out cross-validation over the external controls, so the data needs at least 2 external controls. The covariates must be numeric or logical; code a factor as 0/1 indicators first.

Usage

scm(
  lambda_min = 0,
  lambda_max = 0.1,
  nlambda = 2L,
  parallel = "no",
  ncpus = 1L,
  bootstrap = 200L,
  bootstrap_ci_type = NULL
)

Arguments

lambda_min: Minimum penalty parameter for LOOCV. A finite number of at least 0.
lambda_max: Maximum penalty parameter for LOOCV. A finite number of at least lambda_min.
nlambda: Number of lambda values to evaluate in LOOCV, evenly spaced from lambda_min to lambda_max. With nlambda = 1, lambda_max must equal lambda_min.
parallel: Parallelization type for bootstrap ("no", "multicore", or "snow").
ncpus: Number of CPUs for parallel bootstrap.
bootstrap: Number of bootstrap replicates (at least 2). Defaults to 200. Use about 1000 or more for reported intervals; small values are for quick checks only, and their interval can exclude the point estimate.
bootstrap_ci_type: Bootstrap CI type: one of "perc" (default), "bca", "norm", or "basic". "bca" is slow when bootstrap is smaller than the number of patients: boot::boot.ci() then refits the estimator once for each patient.

Value

An S4 object of class scm_method.

Details

The analysis result from run_analysis() has an attribute "lambda", the penalty that cross-validation selected: attr(result, "lambda").

References

Zhou et al. (2024). Estimating treatment effect in randomized trial after control to treatment crossover using external controls. Journal of Biopharmaceutical Statistics. doi:10.1080/10543406.2024.2330209

Examples

scm(lambda_min = 0, lambda_max = 0.001, nlambda = 2, bootstrap = 50)
#> An object of class "scm_method"
#> Slot "lambda_min":
#> [1] 0
#> 
#> Slot "lambda_max":
#> [1] 0.001
#> 
#> Slot "nlambda":
#> [1] 2
#> 
#> Slot "parallel":
#> [1] "no"
#> 
#> Slot "ncpus":
#> [1] 1
#> 
#> Slot "method_name":
#> [1] "SCM"
#> 
#> Slot "bootstrap":
#> [1] 50
#> 
#> Slot "bootstrap_ci_type":
#> [1] "perc"
#>