Compute NCA for multiple intervals

Usage

pk.nca.intervals(
  data_conc,
  data_dose,
  data_intervals,
  options,
  impute,
  data_sparse_conc = NULL,
  verbose = FALSE,
  timeu = NULL,
  warning_prefix = ""
)

Arguments

data_conc: A data.frame or tibble with standardized column names as output from prepare_PKNCAconc(). With sparse PK this is the arithmetic-mean profile.
data_dose: A data.frame or tibble with standardized column names as output from prepare_PKNCAdose()
data_intervals: A data.frame or tibble with standardized column names as output from prepare_PKNCAintervals()
options: List of changes to the default PKNCA options (see PKNCA.options())
impute: The column name in data_intervals to use for imputation
data_sparse_conc: For sparse PK, a data.frame or tibble of the pooled individual samples (including a subject column) as output from prepare_PKNCAconc(); NULL for dense PK
verbose: Indicate, by message(), the current state of calculation.
timeu: The time unit of the group's times: NULL when it is not known, which is taken to be hours, or NA when it cannot be used. A \(\tau\) detected from the dose times is matched to the nominal dosing intervals for that unit (see find.dose.regimen()).
warning_prefix: The text naming the group, put before each dose regimen warning

Value

A list with elements "dense" and "sparse", each a data.frame of the NCA results calculated from that concentration representation (or, when no calculation was possible at all, the warning condition saying why)