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Add Subperiod, Period, or Phase Variables to ADSL

Source: R/period_dataset.R
derive_vars_period.Rd

The function adds subperiod, period, or phase variables like P01S1SDT, P01S2SDT, AP01SDTM, AP02SDTM, TRT01A, TRT02A, PH1SDT, PH2SDT, ... to the input dataset. The values of the variables are defined by a period reference dataset which has one observations per patient and subperiod, period, or phase.

Usage

derive_vars_period(
  dataset,
  dataset_ref,
  new_vars,
  subject_keys = get_admiral_option("subject_keys")
)

Arguments

dataset

Input dataset

The variables specified by the subject_keys argument are expected to be in the dataset.

dataset_ref

Period reference dataset

The variables specified by new_vars and subject_keys are expected.

If subperiod variables are requested, APERIOD and ASPER are expected. If period variables are requested. APERIOD is expected. If phase variables are requested, APHASEN is expected.

new_vars

New variables

A named list of variables like exprs(PHwSDT = PHSDT, PHwEDT = PHEDT, APHASEw = APHASE) is expected. The left hand side of the elements defines a set of variables (in CDISC notation) to be added to the output dataset. The right hand side defines the source variable from the period reference dataset.

If the lower case letter "w" is used it refers to a phase variable, if the lower case letters "xx" are used it refers to a period variable, and if both "xx" and "w" are used it refers to a subperiod variable.

Only one type must be used, e.g., all left hand side values must refer to period variables. It is not allowed to mix for example period and subperiod variables. If period and subperiod variables are required, separate calls must be used.

subject_keys

Variables to uniquely identify a subject

A list of expressions where the expressions are symbols as returned by exprs() is expected.

Value

The input dataset with subperiod/period/phase variables added (see "Details" section)

Details

For each subperiod/period/phase in the period reference dataset and each element in new_vars a variable (LHS value of new_vars) is added to the output dataset and set to the value of the source variable (RHS value of new_vars.

See also

create_period_dataset()

ADSL Functions that returns variable appended to dataset: derive_var_age_years(), derive_vars_aage(), derive_vars_extreme_event()

Examples

library(tibble)
library(dplyr, warn.conflicts = FALSE)
library(lubridate)

adsl <- tibble(STUDYID = "xyz", USUBJID = c("1", "2"))

# Add period variables to ADSL
period_ref <- tribble(
  ~USUBJID, ~APERIOD, ~APERSDT,     ~APEREDT,
  "1",             1, "2021-01-04", "2021-02-06",
  "1",             2, "2021-02-07", "2021-03-07",
  "2",             1, "2021-02-02", "2021-03-02",
  "2",             2, "2021-03-03", "2021-04-01"
) %>%
  mutate(
    STUDYID = "xyz",
    APERIOD = as.integer(APERIOD),
    across(matches("APER[ES]DT"), ymd)
  )

derive_vars_period(
  adsl,
  dataset_ref = period_ref,
  new_vars = exprs(APxxSDT = APERSDT, APxxEDT = APEREDT)
) %>%
  select(STUDYID, USUBJID, AP01SDT, AP01EDT, AP02SDT, AP02EDT)
#> # A tibble: 2 × 6
#>   STUDYID USUBJID AP01SDT    AP01EDT    AP02SDT    AP02EDT   
#>   <chr>   <chr>   <date>     <date>     <date>     <date>    
#> 1 xyz     1       2021-01-04 2021-02-06 2021-02-07 2021-03-07
#> 2 xyz     2       2021-02-02 2021-03-02 2021-03-03 2021-04-01

# Add phase variables to ADSL
phase_ref <- tribble(
  ~USUBJID, ~APHASEN, ~PHSDT,       ~PHEDT,       ~APHASE,
  "1",             1, "2021-01-04", "2021-02-06", "TREATMENT",
  "1",             2, "2021-02-07", "2021-03-07", "FUP",
  "2",             1, "2021-02-02", "2021-03-02", "TREATMENT"
) %>%
  mutate(
    STUDYID = "xyz",
    APHASEN = as.integer(APHASEN),
    across(matches("PH[ES]DT"), ymd)
  )

derive_vars_period(
  adsl,
  dataset_ref = phase_ref,
  new_vars = exprs(PHwSDT = PHSDT, PHwEDT = PHEDT, APHASEw = APHASE)
) %>%
  select(STUDYID, USUBJID, PH1SDT, PH1EDT, PH2SDT, PH2EDT, APHASE1, APHASE2)
#> # A tibble: 2 × 8
#>   STUDYID USUBJID PH1SDT     PH1EDT     PH2SDT     PH2EDT     APHASE1   APHASE2
#>   <chr>   <chr>   <date>     <date>     <date>     <date>     <chr>     <chr>  
#> 1 xyz     1       2021-01-04 2021-02-06 2021-02-07 2021-03-07 TREATMENT FUP    
#> 2 xyz     2       2021-02-02 2021-03-02 NA         NA         TREATMENT NA     

# Add subperiod variables to ADSL
subperiod_ref <- tribble(
  ~USUBJID, ~APERIOD, ~ASPER, ~ASPRSDT,     ~ASPREDT,
  "1",             1,      1, "2021-01-04", "2021-01-19",
  "1",             1,      2, "2021-01-20", "2021-02-06",
  "1",             2,      1, "2021-02-07", "2021-03-07",
  "2",             1,      1, "2021-02-02", "2021-03-02",
  "2",             2,      1, "2021-03-03", "2021-04-01"
) %>%
  mutate(
    STUDYID = "xyz",
    APERIOD = as.integer(APERIOD),
    ASPER = as.integer(ASPER),
    across(matches("ASPR[ES]DT"), ymd)
  )

derive_vars_period(
  adsl,
  dataset_ref = subperiod_ref,
  new_vars = exprs(PxxSwSDT = ASPRSDT, PxxSwEDT = ASPREDT)
) %>%
  select(STUDYID, USUBJID, P01S1SDT, P01S1EDT, P01S2SDT, P01S2EDT, P02S1SDT, P02S1EDT)
#> # A tibble: 2 × 8
#>   STUDYID USUBJID P01S1SDT   P01S1EDT   P01S2SDT   P01S2EDT   P02S1SDT  
#>   <chr>   <chr>   <date>     <date>     <date>     <date>     <date>    
#> 1 xyz     1       2021-01-04 2021-01-19 2021-01-20 2021-02-06 2021-02-07
#> 2 xyz     2       2021-02-02 2021-03-02 NA         NA         2021-03-03
#> # ℹ 1 more variable: P02S1EDT <date>