Takes information about columns in dataset and constructs the dosing records.
Usage
dose_records_builder(
NCA_DS = NULL,
dose_from = NULL,
col_id = NULL,
col_time = NULL,
col_ntime = NULL,
col_route = NULL,
col_dose = NULL,
col_cycle = NULL,
col_dur = NULL,
col_evid = NULL,
col_analyte = NULL,
col_group = NULL
)Arguments
- NCA_DS
Dataset containing dosing records.
- dose_from
Method of dose extraction either "cols" or "rows".
- col_id
Name of column with subject ID.
- col_time
Name of column with time since first dose.
- col_ntime
Name of column with time since the last dose (required with
dose_from="cols").- col_route
Name of column with route information.
- col_dose
Name of column with last dose given.
- col_cycle
Name of column with dose cycle (required with
dose_from="cols").- col_dur
Name of column with dose duration.
- col_evid
Name of column with event ID (required with
dose_from="rows").- col_analyte
Name of column with analyte (optional).
- col_group
Names of columns with grouping information (optionl).
Value
list containing the following elements
isgood: Return status of the function.
msgs: Messages to be passed back to the user.
dose_rec:
Examples
if(system.file(package="readxl") !=""){
library(dplyr)
library(readxl)
library(stringr)
# Example data file:
data_file = system.file(package="formods","test_data","TEST_DATA.xlsx")
# Dataset formatted to extract dosing from columns
DS_cols = readxl::read_excel(path=data_file, sheet="DATA") |>
dplyr::filter(EVID == 0) |>
dplyr::filter(DOSE %in% c(3)) |>
dplyr::filter(str_detect(string=Cohort, "^MD")) |>
dplyr::filter(CMT == "C_ng_ml")
drb_res = dose_records_builder(
NCA_DS = DS_cols,
dose_from = "cols",
col_id = "ID",
col_time = "TIME_DY",
col_ntime = "NTIME_DY",
col_route = "ROUTE",
col_cycle = "DOSE_NUM",
col_dose = "DOSE",
col_group = "Cohort")
utils::head(drb_res$dose_rec)
# Dataset formatted to extract dosing from rows (records)
DS_rows = readxl::read_excel(path=data_file, sheet="DATA") |>
dplyr::filter(DOSE %in% c(3)) |>
dplyr::filter(str_detect(string=Cohort, "^MD")) |>
dplyr::filter(CMT %in% c("Ac", "C_ng_ml"))
drb_res = dose_records_builder(
NCA_DS = DS_rows,
dose_from = "rows",
col_id = "ID",
col_time = "TIME_DY",
col_ntime = "NTIME_DY",
col_route = "ROUTE",
col_dose = "AMT",
col_evid = "EVID",
col_group = "Cohort")
utils::head(drb_res$dose_rec)
}
#>
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#>
#> filter, lag
#> The following objects are masked from ‘package:base’:
#>
#> intersect, setdiff, setequal, union
#> # A tibble: 0 × 5
#> # ℹ 5 variables: ID <dbl>, TIME_DY <dbl>, AMT <dbl>, ROUTE <chr>, Cohort <chr>