pmrm_simulate: Simulate data.

In pmrm: Progression Models for Repeated Measures

Simulate data.

Description

Simulate data from a progression model for repeated measures.

Usage

pmrm_simulate(
  patients,
  visit_times,
  spline_knots,
  spline_method,
  tau,
  alpha,
  beta,
  gamma,
  sigma,
  rho,
  slowing,
  proportional
)

Arguments

patients	Positive integer scalar, total number of patients in the output dataset. Patients are allocated (roughly) uniformly across the study arms.
visit_times	Numeric vector, the continuous scheduled time after randomization of each study visit.
spline_knots	Numeric vector of spline knots on the continuous scale, including boundary knots.
spline_method	Character string, spline method to use for the base model. Must be "natural" or "fmm". See stats::splinefun() for details.
tau	Positive numeric scalar, standard deviation for jittering the simulated time points. Defaults to 0 so that the observed continuous times are just the scheduled visit times.
alpha	Numeric vector of spline coefficients for simulating the mean function ⁠f(t_{ij} | spline_knots, alpha)⁠. Must have length(spline_knots) elements.
beta	Treatment effect parameters. Input format and interpretation vary from model to model.
gamma	Numeric vector of model coefficients for covariate adjustment. The simulation functions in pmrm simulate length(gamma) columns for the covariate adjustment model matrix W. Set to numeric(0) to omit covariates.
sigma	A positive numeric vector of visit-level standard deviation parameters.
rho	A finite numeric vector of correlation parameters. Must have length J * (J - 1) / 2, where J is length(visit_times). The full covariance matrix Sigma is given by diag(sigma) %*% RTMB::unstructured(length(sigma))$corr(rho) %*% diag(sigma).

Value

A tibble with simulated clinical data (see the "Simulated data" section).

Simulated data

The datasets returned from the simulation functions have one row per patient visit and the following columns which conform to the notation from vignette("models", package = "pmrm"):

• patient: Character vector of patient ID labels.

• visit: Ordered factor of clinical visits with labels included. min(visit) indicates the baseline visit.

• arm: Ordered factor of study arms with visits included. min(arm) indicates the control arm.

• i: integer ID of each patient.

• j: integer ID of each clinical visit. j == 1 at baseline.

• k: integer ID of the study arm of patient i. k == 1 for the control arm.

• y: clinical outcomes.

• t: observed continuous time since baseline.

• beta: the scalar component of the treatment effect parameter beta defined for patient i.

• mu: expected clinical outcome at the given patient visit.

• ⁠w_*⁠: columns of the covariate adjustment model matrix W.

• e: residuals.

pmrm documentation built on March 12, 2026, 5:07 p.m.