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Generate a synthetic PMX event table from a structural model

Source: R/generate_structural.R
dot-generate_structural.Rd

Works in two modes. Supplied a pmx_structural_model() it generates purely from public inputs, reads no confidential data, and makes no privacy claim. Supplied a .fit_calibrated() result it uses the privately corrected parameters; that is post-processing and consumes no further budget.

Usage

.generate_structural(
  x,
  design = NULL,
  n_subjects = NULL,
  seed = NULL,
  dropout = 0,
  lloq = NULL,
  covariates = NULL
)

Arguments

x

A pmx_structural_model or a pmx_calibrated_model.

design

A pmx_trial_design(). Taken from x when it is a calibrated model.

n_subjects

Number of subjects. Defaults to the planned cohort total, or to the released private count for a calibrated model.

seed

Ordinary generation seed. Unrelated to privacy noise.

dropout

Fraction of subjects who discontinue early. A public assumption from the protocol.

lloq

Lower limit of quantification. Observations below it are flagged CENS = 1 with DV at the limit, following the Monolix convention.

covariates

Optional pmx_covariates() for prior-mode generation. Ignored for a calibrated model, which carries its own released covariate summaries.

Value

A data frame in PMX event-table form.