NMsim (version 0.2.1)

NMaddSamples: Add simulation (sample) 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. This function was previously called `addEVID2()`.

Usage

NMaddSamples(
  data,
  TIME,
  TAPD,
  CMT,
  EVID,
  DV,
  col.id = "ID",
  args.NMexpandDoses,
  unique = TRUE,
  extras.are.covs = TRUE,
  quiet = FALSE,
  as.fun,
  doses,
  time.sim
)

Value

A data.frame with dosing records

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. Required if `CMT` is a column in `data`. 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.

DV

Optionally provide a single value to be assigned to the `DV` column. The default is to assign nothing which will result in `NA` as samples are stacked (`rbind`) with `data`. If you assign a different value in `DV`, the default value of `EVID` changes to `0`, and `MDV` will be `0` instead of `1`. An example where this is useful is when generating datasets for `$DESIGN` where `DV=0` is often used.

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, `NMaddSamples()` will use `NMdata::NMexpanDoses()` to evaluate the time of each dose. Other than the `data` argument, `NMaddSamples()` 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 `NMaddSamples()`.

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 `NMaddSamples()` clean them. If you want to keep your duplicated events, use `unique=FALSE`.

extras.are.covs

If TIME and/or `TAPD` are `data.frame`s and contain other columns than `TIME` and/or `TAPD`, those are by default assumed to be subject-level covariates to be merged with data. More specifically, they will be merged by when the sample times are added. If `extras.are.covs=FALSE`, they will not be merged by. Instead, they will be kept as additional columns with specified values, aligned with the sample times. See examples.

quiet

Suppress messages? Default is `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.

Examples

(doses1 <- NMcreateDoses(TIME=c(0,12,24,36),AMT=c(2,1)))
NMaddSamples(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 <- NMaddSamples(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(0,3))
seq.time.md <- data.frame(regimen="MD",TIME=c(0,12,24))
seq.time <- rbind(seq.time.sd,seq.time.md)
NMaddSamples(dt.doses,TIME=seq.time,CMT=2)

## All subjects get all samples (extras.are.covs=FALSE)
NMaddSamples(dt.doses,TIME=seq.time,extras.are.covs=FALSE,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 <- NMaddSamples(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)
NMaddSamples(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)
NMaddSamples(df.doses,TIME=seq.time,TAPD=3,CMT=2)

## Using a custom DV value affects EVID and MDV 
df.doses <- NMcreateDoses(TIME=c(0,12),AMT=10,CMT=1)
seq.time <- c(4)
NMaddSamples(df.doses,TAPD=seq.time,CMT=2,DV=0)