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LongitudinalGSF

Source: R/LongitudinalGSF.R
LongitudinalGSF-class.Rd

This class extends the general LongitudinalModel class for using the Generalized Stein-Fojo (GSF) model for the longitudinal outcome.

Usage

LongitudinalGSF(
  mu_bsld = prior_normal(log(60), 1),
  mu_ks = prior_normal(log(0.5), 1),
  mu_kg = prior_normal(log(0.3), 1),
  mu_phi = prior_normal(qlogis(0.5), 1),
  omega_bsld = prior_lognormal(log(0.2), 1),
  omega_ks = prior_lognormal(log(0.2), 1),
  omega_kg = prior_lognormal(log(0.2), 1),
  omega_phi = prior_lognormal(log(0.2), 1),
  sigma = prior_lognormal(log(0.1), 1),
  scaled_variance = TRUE,
  centred = FALSE
)

Arguments

mu_bsld

(Prior)
for the mean baseline value mu_bsld.

mu_ks

(Prior)
for the mean shrinkage rate mu_ks.

mu_kg

(Prior)
for the mean growth rate mu_kg.

mu_phi

(Prior)
for the mean proportion of cells affected by the treatment mu_phi.

omega_bsld

(Prior)
for the baseline value standard deviation omega_bsld.

omega_ks

(Prior)
for the shrinkage rate standard deviation omega_ks.

omega_kg

(Prior)
for the growth rate standard deviation omega_kg.

omega_phi

(Prior)
for the standard deviation of the proportion of cells affected by the treatment omega_phi.

sigma

(Prior)
for the variance of the longitudinal values sigma.

scaled_variance

(logical)
whether the variance should be scaled by the expected value (see the "Statistical Specifications" vignette for more details)

centred

(logical)
whether to use the centred parameterization.