Sparse estimators for the AUC and AUMC to infinity

These are the FUN_sparse of aucinf.obs and aumcinf.obs: with sparse PK, pk.nca() estimates them as the sparse AUClast or AUMClast (see pk.calc.auclast_sparse()) plus the extrapolation from the mean concentration at tlast with the lambda.z of the mean profile, with the standard error of Yuan (1993) and its extension to the AUMC. The sparse_lambda_z_se option of PKNCA.options() chooses whether the standard error adds the uncertainty of lambda.z with the delta method ("delta", the default) or treats it as known ("none", Yuan's method); see vignette("v24-sparse-auc-to-infinity").

Usage

pk.calc.aucinf.obs_sparse(
  conc,
  time,
  subject,
  lambda.z,
  lambda.z.time.first,
  lambda.z.time.last,
  lambda.z.n.points,
  ...,
  options = list()
)

pk.calc.aumcinf.obs_sparse(
  conc,
  time,
  subject,
  lambda.z,
  lambda.z.time.first,
  lambda.z.time.last,
  lambda.z.n.points,
  ...,
  options = list()
)

Arguments

conc

Measured concentrations

time

Time of the measurement of the concentrations

subject

Subject identifiers (may be any class; may not be null). A missing subject marks an imputed concentration (such as the zero that the start_conc0 imputation adds at the start of an interval): a time where every subject is missing has a known concentration, which enters sparse estimates but not their variance.

lambda.z

The elimination rate of the mean profile

lambda.z.time.first, lambda.z.time.last, lambda.z.n.points

The first and last time and the number of points of the half-life fit to the mean profile

...

For functions other than pk.calc.auxc, these values are passed to pk.calc.auxc

options

List of changes to the default PKNCA options (see PKNCA.options())

Value

A data.frame with the point estimate, its standard error, and the degrees of freedom, named for the parameter (aucinf.obs, aucinf.obs_se, and aucinf.obs_df, or the aumcinf.obs equivalents)

Functions

• pk.calc.aumcinf.obs_sparse(): Sparse AUMCinf,obs

References

Yuan J. Estimation of variance for AUC in animal studies. Journal of Pharmaceutical Sciences. 1993;82(7):761-763. doi:10.1002/jps.2600820718

See also

Other Sparse Methods: as_sparse_pk(), pk.calc.aucivlast_sparse(), pk.calc.auclast_sparse(), pk.calc.sparse_auc(), pk.calc.sparse_aumc(), sparse_auc_weight_linear(), sparse_bootstrap(), sparse_mean(), summary.PKNCAresults_sparse_bootstrap()