Fitting an MMRM with Single Optimizer — fit_single

This function helps to fit an MMRM using TMB with a single optimizer, while capturing messages and warnings.

fit_single_optimizer(
  formula,
  data,
  weights,
  reml = TRUE,
  covariance = NULL,
  tmb_data,
  formula_parts,
  ...,
  control = mmrm_control(...)
)

Arguments

formula: (formula)
the model formula, see details.
data: (data)
the data to be used for the model.
weights: (vector)
an optional vector of weights to be used in the fitting process. Should be NULL or a numeric vector.
reml: (flag)
whether restricted maximum likelihood (REML) estimation is used, otherwise maximum likelihood (ML) is used.
covariance: (cov_struct)
a covariance structure type definition as produced with cov_struct(), or value that can be coerced to a covariance structure using as.cov_struct(). If no value is provided, a structure is derived from the provided formula.
tmb_data: (mmrm_tmb_data)
object.
formula_parts: (mmrm_tmb_formula_parts)
object.
...: Additional arguments to pass to mmrm_control().
control: (mmrm_control)
object.

Value

The mmrm_fit object, with additional attributes containing warnings, messages, optimizer used and convergence status in addition to the mmrm_tmb contents.

Details

fit_single_optimizer will fit the mmrm model using the control provided. If there are multiple optimizers provided in control, only the first optimizer will be used. If tmb_data and formula_parts are both provided, formula, data, weights, reml, and covariance are ignored.

Examples

mod_fit <- fit_single_optimizer(
  formula = FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID),
  data = fev_data,
  weights = rep(1, nrow(fev_data)),
  optimizer = "nlminb"
)
attr(mod_fit, "converged")
#> [1] TRUE