Returns a tibble containing parameter estimates from a
bbi_{.model_type}_summary object. Details about the tibble that is returned
are in the return value section below. Note: if you need to pull in the
parameter estimates for a large number of NONMEM models at once, consider
using param_estimates_batch() instead.
param_estimates(.summary, .alpha)
# S3 method for bbi_nonmem_summary
param_estimates(.summary, .alpha = NULL)A bbi_{.model_type}_summary object.
numeric. If specified, return the p-value for each eta value on the diagonal, as well as whether they are below the specified value of alpha. Defaults to NULL.
Returns a tibble with the following columns:
parameter_names -- Parameter name ("THETA1", "THETA2", etc.)
estimate -- Parameter estimate
stderr -- Standard Error
random_effect_sd -- OMEGA and SIGMA elements in standard deviation/correlation format
random_effect_sdse -- Standard errors to the OMEGA and SIGMA elements in standard deviation/correlation format
fixed -- TRUE if parameter is fixed, FALSE otherwise
diag -- TRUE if parameter is a diagonal element in random effect matrix, FALSE if off-diagonal, NA if parameter is a THETA
shrinkage -- Shrinkage for final estimation method, using SD parameterization (for NONMEM this is ETAshrinkSD and EPSshrinkSD).
The shrinkage using Variance Parameterization, as well as for other estimation methods and multiple subpops if present,
can be found in bbi_nonmem_summary$shrinkage_details.
Note that Bayesian methods are not yet supported by this function. Creating a parameter table
like this for Bayesian estimation methods requires a different approach, which has not yet been
implemented. If the final estimation method of the input model is Bayesian, a not implemented
error will be thrown.
param_estimates(bbi_nonmem_summary): Takes bbi_nonmem_summary object, the output of model_summary.bbi_nonmem_model().