adm_rows: Add administration lines to a dataset

In mapbayr: MAP-Bayesian Estimation of PK Parameters

Add administration lines to a dataset

Description

The adm_rows() function adds an one or several administration lines to a dataset provided as a proper data.frame or within a 'mrgsolve' model. Used in combination with obs_rows() and add_covariates(), it helps the creation of datasets in the proper format for simulations with 'mrgsolve' or parameter estimation with 'mapbayr', as explained in data_helpers.

Usage

adm_rows(x, ...)

## S3 method for class 'data.frame'
adm_rows(
  x,
  ID = NULL,
  time = NULL,
  evid = 1L,
  cmt,
  amt,
  mdv = 1L,
  addl = NULL,
  ss = NULL,
  ii = NULL,
  rate = NULL,
  .datehour = NULL,
  ...
)

## S3 method for class 'missing'
adm_rows(...)

## S3 method for class 'mrgmod'
adm_rows(x, cmt = adm_cmt(x), rate = NULL, ...)

Arguments

x	either a data.frame or a 'mrgsolve' model object
...	additional columns or arguments for mrgsolve::ev()
ID	subject ID (default is 1)
time	event time. Default is 0 if no previous events. Mind consistency with .datehour.
evid	event identification (default is 1 for administration, 0 for observation)
cmt	compartment (no default, except if ⁠[ADM]⁠ was tagged in the ⁠$CMT⁠ block in model code. See examples.)
amt	dose amount (for administration records only)
mdv	missing dependent value (default is 1 for administration records)
addl	additional dose (optional)
ss	steady-state (optional, is this dose the last of an infinity of administration? Yes, 1, or no, 0)
ii	inter-dose interval (optional, use it with ss and addl)
rate	rate of administration (optional, set to -2 if you model zero-order infusion. See examples.)
.datehour	a object of class POSIXct, a number or a character vector that can be passed to parse_datehour(). Using .datehour will update the value of time in the dataset, with units in hours. Mind consistency with the time argument.

Value

a data.frame, or a 'mrgsolve' model with a dataset in the ⁠@args$data⁠ slot (accessible with get_data()).

See Also

data_helpers

Examples

# Create a dataset from scratch
adm_rows(amt = 100, cmt = 1)

# Pipe-friendly addition of administration record to a pre-existing dataset
library(magrittr)
adm_rows(amt = 100, cmt = 1) %>%
  adm_rows(time = 3, amt = 200, cmt = 1, addl = 3, ii = 1)

# Inform times using the `.datehour` argument:
adm_rows(.datehour = "2020-01-01 11:11", amt = 100, cmt = 1) %>%
  adm_rows(.datehour = "2020-01-02 22:22", amt = 200, cmt = 1) %>%
  adm_rows(time = 48, amt = 300, cmt = 1)

# Start from a 'mrgsolve' model
library(mrgsolve)
house() %>%
  adm_rows(amt = 100, cmt = 1) %>%
  adm_rows(time = 3, amt = 200, cmt = 1, addl = 3, ii = 1) %>%
  mrgsim(delta = 1)

# Default administration compartments
# Set default administration compartments in the code with `[ADM]`
model <- mcode("model", "
$CMT @annotated
DEPOT : Depot [ADM]
CENTR : Central
", compile = FALSE)
adm_cmt(model)

# Thus, no need to manually specify `cmt = 1` anymore.
model %>%
  adm_rows(amt = 100) %>%
  adm_rows(time = 3, amt = 200, addl = 3, ii = 1) %>%
  get_data()

# Automatic lines duplication if multiple depot compartments
# Automatic `rate = -2` increment if model with 0-order absorption
model <- mcode("model", "
$PARAM DUR = 1.0
$CMT @annotated
DEPOT : Depot [ADM]
CENTR : Central [ADM]
$MAIN
D_CENTR = DUR ;
", compile = FALSE)
adm_cmt(model)

model %>%
  adm_rows(amt = 100) %>%
  adm_rows(time = 3, amt = 200, addl = 3, ii = 1) %>%
  get_data()

mapbayr documentation built on July 26, 2023, 5:16 p.m.