Simulate a Claret-Bruno longitudinal model with covariates

Usage

SimLongitudinalClaretBrunoCov(
  times = c(-100, -50, 0, 50, 100, 150, 250, 350, 450, 550)/365,
  mu_b_formula = ~study,
  omega_b_formula = ~study,
  mu_g_formula = ~arm,
  omega_g_formula = ~arm,
  mu_c_formula = ~arm,
  omega_c_formula = ~arm,
  mu_p_formula = ~arm,
  omega_p_formula = ~arm,
  mu_b_parametrization = "linear",
  omega_b_parametrization = "log-linear",
  mu_g_parametrization = "linear",
  omega_g_parametrization = "log-linear",
  mu_c_parametrization = "linear",
  omega_c_parametrization = "log-linear",
  mu_p_parametrization = "linear",
  omega_p_parametrization = "log-linear",
  mu_b_intercept = log(60),
  mu_b_coefficients = numeric(),
  omega_b_intercept = log(0.2),
  omega_b_coefficients = numeric(),
  mu_g_intercept = log(1),
  mu_g_coefficients = numeric(),
  omega_g_intercept = log(0.2),
  omega_g_coefficients = numeric(),
  mu_c_intercept = log(0.4),
  mu_c_coefficients = numeric(),
  omega_c_intercept = log(0.2),
  omega_c_coefficients = numeric(),
  mu_p_intercept = log(2),
  mu_p_coefficients = numeric(),
  omega_p_intercept = log(0.2),
  omega_p_coefficients = numeric(),
  sigma = 0.01,
  link_dsld = 0,
  link_ttg = 0,
  link_identity = 0,
  link_growth = 0,
  scaled_variance = FALSE
)

Arguments

times: (numeric) Observation times.
mu_b_formula: (formula) One-sided formula for subject-level covariate effects on the baseline tumour size mean.
omega_b_formula: (formula) One-sided formula for subject-level covariate effects on the baseline tumour size standard deviation.
mu_g_formula: (formula) One-sided formula for subject-level covariate effects on the growth mean.
omega_g_formula: (formula) One-sided formula for subject-level covariate effects on the growth standard deviation.
mu_c_formula: (formula) One-sided formula for subject-level covariate effects on the resistance mean.
omega_c_formula: (formula) One-sided formula for subject-level covariate effects on the resistance standard deviation.
mu_p_formula: (formula) One-sided formula for subject-level covariate effects on the growth inhibition mean.
omega_p_formula: (formula) One-sided formula for subject-level covariate effects on the growth inhibition standard deviation.
mu_b_parametrization: (character) Parametrization of the baseline tumour size mean predictor.
omega_b_parametrization: (character) Parametrization of the baseline tumour size standard deviation predictor. Only "exponential" and "log-linear" are supported.
mu_g_parametrization: (character) Parametrization of the growth mean predictor.
omega_g_parametrization: (character) Parametrization of the growth standard deviation predictor. Only "exponential" and "log-linear" are supported.
mu_c_parametrization: (character) Parametrization of the resistance mean predictor.
omega_c_parametrization: (character) Parametrization of the resistance standard deviation predictor. Only "exponential" and "log-linear" are supported.
mu_p_parametrization: (character) Parametrization of the growth inhibition mean predictor.
omega_p_parametrization: (character) Parametrization of the growth inhibition standard deviation predictor. Only "exponential" and "log-linear" are supported.
mu_b_intercept: (numeric) Intercept for the baseline tumour size mean predictor.
mu_b_coefficients: (numeric) Covariate coefficients for the baseline tumour size mean predictor.
omega_b_intercept: (numeric) Intercept for the baseline tumour size standard deviation predictor.
omega_b_coefficients: (numeric) Covariate coefficients for the baseline tumour size standard deviation predictor.
mu_g_intercept: (numeric) Intercept for the growth mean predictor.
mu_g_coefficients: (numeric) Covariate coefficients for the growth mean predictor.
omega_g_intercept: (numeric) Intercept for the growth standard deviation predictor.
omega_g_coefficients: (numeric) Covariate coefficients for the growth standard deviation predictor.
mu_c_intercept: (numeric) Intercept for the resistance mean predictor.
mu_c_coefficients: (numeric) Covariate coefficients for the resistance mean predictor.
omega_c_intercept: (numeric) Intercept for the resistance standard deviation predictor.
omega_c_coefficients: (numeric) Covariate coefficients for the resistance standard deviation predictor.
mu_p_intercept: (numeric) Intercept for the growth inhibition mean predictor.
mu_p_coefficients: (numeric) Covariate coefficients for the growth inhibition mean predictor.
omega_p_intercept: (numeric) Intercept for the growth inhibition standard deviation predictor.
omega_p_coefficients: (numeric) Covariate coefficients for the growth inhibition standard deviation predictor.
sigma: (numeric) Observation-error standard deviation.
link_dsld: (numeric) Coefficient for the DSLD association link.
link_ttg: (numeric) Coefficient for the TTG association link.
link_identity: (numeric) Coefficient for the identity association link.
link_growth: (numeric) Coefficient for the growth association link.
scaled_variance: (logical) Whether to use multiplicative observation error.

Value

A SimLongitudinalClaretBrunoCov object.