addEVID2: Add simulation records to dosing records

In NMsim: Seamless 'Nonmem' Simulation Platform

Add simulation records to dosing records

Description

Adds simulation events to all subjects in a data set. Copies over columns that are not varying at subject level (i.e. non-variying covariates). Can add simulation events relative to previous dosing time.

Usage

addEVID2(
  data,
  TIME,
  TAPD,
  CMT,
  EVID = 2,
  col.id = "ID",
  args.NMexpandDoses,
  unique = TRUE,
  as.fun,
  doses,
  time.sim
)

Arguments

data	Nonmem-style data set. If using 'TAPD' an 'EVID' column must contain 1 for dosing records.
TIME	A numerical vector with simulation times. Can also be a data.frame in which case it must contain a 'TIME' column and is merged with 'data'.
TAPD	A numerical vector with simulation times, relative to previous dose. When this is used, 'data' must contain rows with 'EVID=1' events and a 'TIME' column. 'TAPD' can also be a data.frame in which case it must contain a 'TAPD' column and is merged with 'data'.
CMT	The compartment in which to insert the EVID=2 records. If longer than one, the records will be repeated in all the specified compartments. If a data.frame, covariates can be specified.
EVID	The value to put in the EVID column for the created rows. Default is 2 but 0 may be prefered even for simulation.
col.id	The name of the column in 'data' that holds the unique subject identifier.
args.NMexpandDoses	Only relevant - and likely not needed - if data contains ADDL and II columns. If those columns are included, 'addEVID2()' will use 'NMdata::NMexpanDoses()' to evaluate the time of each dose. Other than the 'data' argument, 'addEVID2()' relies on the default 'NMexpanDoses()' argument values. If this is insufficient, you can specify other argument values in a list, or you can call 'NMdata::NMexpanDoses()' manually before calling 'addEVID2()'.
unique	If 'TRUE' (default), events are reduced to unique time points before insertion. Sometimes, it's easier to combine sequences of time points that overlap (maybe across 'TIME' and 'TAPD'), and let 'addEVID2()' clean them. If you want to keep your duplicated events, use 'unique=FALSE'.
as.fun	The default is to return data as a data.frame. Pass a function (say 'tibble::as_tibble') in as.fun to convert to something else. If data.tables are wanted, use as.fun="data.table". The default can be configured using NMdataConf.
doses	Deprecated. Use 'data'.
time.sim	Deprecated. Use 'TIME'.

Details

The resulting data set is ordered by ID, TIME, and EVID. You may have to reorder for your specific needs.

Value

A data.frame with dosing records

Examples

(doses1 <- NMcreateDoses(TIME=c(0,12,24,36),AMT=c(2,1)))
addEVID2(doses1,TIME=seq(0,28,by=4),CMT=2)

## two named compartments
dt.doses <- NMcreateDoses(TIME=c(0,12),AMT=10,CMT=1)
seq.time <- c(0,4,12,24)
dt.cmt <- data.frame(CMT=c(2,3),analyte=c("parent","metabolite"))
res <- addEVID2(dt.doses,TIME=seq.time,CMT=dt.cmt)

## Separate sampling schemes depending on covariate values
dt.doses <- NMcreateDoses(TIME=data.frame(regimen=c("SD","MD","MD"),TIME=c(0,0,12)),AMT=10,CMT=1)

seq.time.sd <- data.frame(regimen="SD",TIME=seq(0,6))
seq.time.md <- data.frame(regimen="MD",TIME=c(0,4,12,24))
seq.time <- rbind(seq.time.sd,seq.time.md)
addEVID2(dt.doses,TIME=seq.time,CMT=2)

## an observed sample scheme and additional simulation times
df.doses <- NMcreateDoses(TIME=0,AMT=50,addl=list(ADDL=2,II=24))
dense <- c(seq(1,3,by=.1),4:6,seq(8,12,by=4),18,24)
trough <- seq(0,3*24,by=24)
sim.extra <- seq(0,(24*3),by=2)
time.all <- c(dense,dense+24*3,trough,sim.extra)
time.all <- sort(unique(time.all))
dt.sample <- data.frame(TIME=time.all)
dt.sample$isobs <- as.numeric(dt.sample$TIME%in%c(dense,trough))
dat.sim <- addEVID2(dt.doses,TIME=dt.sample,CMT=2)

## TAPD - time after previous dose
df.doses <- NMcreateDoses(TIME=c(0,12),AMT=10,CMT=1)
seq.time <- c(0,4,12,24)
addEVID2(df.doses,TAPD=seq.time,CMT=2)

## TIME and TAPD
df.doses <- NMcreateDoses(TIME=c(0,12),AMT=10,CMT=1)
seq.time <- c(0,4,12,24)
addEVID2(df.doses,TIME=seq.time,TAPD=3,CMT=2)

NMsim documentation built on Nov. 2, 2024, 9:06 a.m.