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Insurance Plasmode Simulation for RESI Evaluation

Source: R/simulations.R
insurancePlasmodeSim.Rd

Runs a plasmode simulation study using the insurance dataset to evaluate RESI confidence interval performance. In each replicate, n observations are resampled with replacement from the full insurance dataset (N = 1338). The RESI point estimates from resi_pe applied to the full dataset are treated as the true parameter values for computing bias, MSE, CI coverage, and CI width.

Usage

insurancePlasmodeSim(
  nsim = 1000L,
  n.vec = c(50, 100, 200, 500, 1000, 2000, 5000),
  nboot = 500L,
  alpha = 0.05,
  ci.method = c("boot", "normal", "qf", "cf"),
  output.dir = NULL,
  fixed.knots = FALSE,
  mc.cores.settings = 1L,
  mc.cores.reps = 1L
)

Arguments

nsim

Integer, number of simulation replicates per (setting, n) cell. Default 1000. Use 10 for initial testing.

n.vec

Integer vector of sample sizes. Default c(50, 100, 200, 500, 1000, 2000, 5000).

nboot

Integer, bootstrap replicates per internal resi call. Default 500. Use 10 for initial testing. Ignored when ci.method != "boot".

alpha

Numeric, CI significance level. Default 0.05.

ci.method

Character, CI method passed to resi. One of "boot" (bootstrap, default), "normal" (asymptotic truncated-normal), or "qf" (asymptotic quadratic-form / Imhof). When ci.method != "boot", nboot is ignored.

output.dir

Character, path to the directory where all results are saved. Created if it does not exist. Defaults to "resiBootSim", "resiAsympNormalSim", or "resiAsympQFSim" based on ci.method when NULL.

fixed.knots

Logical. If TRUE, spline knots are fixed at the empirical tertiles of age in the full insurance dataset rather than re-selected by df = 3 in each bootstrap sample. Default FALSE.

mc.cores.settings

Integer, cores for the outer mclapply over (setting \(\times\) sample size) combinations. Default 1.

mc.cores.reps

Integer, cores for the inner mclapply over simulation replicates within each (setting, n) cell. Default 1.

Value

Invisibly returns the summary metrics data.frame. Side effects:

  • output.dir/sim_raw/<setting>_n<n>.rds: list of per-replicate anova and coefficients tables.

  • output.dir/summary_table.rds: combined metrics table with columns model, vcov, n, n_success, table, term, bias, mse, coverage, width.

Details

Two models are evaluated:

  • lm: log10(charges) ~ ns(age, df=3) * sex + bmi + smoker + region

  • glm: I(charges > 10000) ~ ns(age, df=3) * sex + bmi + smoker + region with family = binomial()

Each model is evaluated under both parametric (vcovfunc = stats::vcov) and robust (vcovfunc = sandwich::vcovHC) variance settings, yielding four simulation conditions.

Parallelization is via mclapply, which uses forking and is not supported on Windows (falls back to sequential evaluation on Windows).

See also

simFigures, simCompareMethodsFigures, resi, resi_pe