Subject-Level Analysis Dataset (ADSL) — radsl • random.cdisc.data

The Subject-Level Analysis Data set (ADSL) is used to provide the variables that describe attributes of a subject. ADSL is a source for subject-level variables used in other analysis data sets, such as population flags and treatment variables. There is only one ADSL per study. ADSL and its related metadata are required in a CDISC-based submission of data from a clinical trial even if no other analysis data sets are submitted.

radsl(
  N = 400,
  study_duration = 2,
  seed = NULL,
  na_percentage = 0,
  na_vars = list(AGE = NA, SEX = NA, RACE = NA, STRATA1 = NA, STRATA2 = NA, BMRKR1 =
    c(seed = 1234, percentage = 0.1), BMRKR2 = c(1234, 0.1), BEP01FL = NA),
  cached = FALSE
)

Arguments

N

Number of patients.

study_duration

Duration of study in years.

seed

Seed for random number generation.

na_percentage

(numeric) Default percentage of values to be replaced by NA

na_vars

(list) A named list where the name of each element is a column name of ds. Each element of this list should be a numeric vector with two elements

seed The seed to be used for this element - can be left NA
percentage How many element should be replaced. 0 is 0 % 1 is 100 %, can be left NA and default percentage is used. This will overwrite default percentage (percentage argument))

cached

boolean whether the cached ADSL data cadsl should be returned or new data should be generated. If set to TRUE then the other arguments to radsl will be ignored.

Value

data.frame

Details

One record per subject.

Keys: STUDYID USUBJID

Examples

library(random.cdisc.data)
radsl(N = 10, study_duration = 2, seed = 1)
#> # A tibble: 10 × 44
#>    STUDYID USUBJID    SUBJID SITEID   AGE AGEU  SEX   RACE  ETHNIC COUNTRY DTHFL
#>    <chr>   <chr>      <chr>  <chr>  <int> <fct> <fct> <fct> <fct>  <fct>   <fct>
#>  1 AB12345 AB12345-C… id-10  CHN-3     35 YEARS M     ASIAN NOT H… CHN     N    
#>  2 AB12345 AB12345-J… id-7   JPN-4     30 YEARS F     ASIAN NOT H… JPN     N    
#>  3 AB12345 AB12345-U… id-3   USA-13    35 YEARS F     AMER… NOT H… USA     N    
#>  4 AB12345 AB12345-B… id-8   BRA-9     31 YEARS F     ASIAN NOT H… BRA     N    
#>  5 AB12345 AB12345-C… id-2   CHN-11    35 YEARS M     BLAC… NOT H… CHN     Y    
#>  6 AB12345 AB12345-C… id-1   CHN-11    35 YEARS F     WHITE UNKNO… CHN     N    
#>  7 AB12345 AB12345-C… id-5   CHN-3     36 YEARS F     ASIAN NOT H… CHN     N    
#>  8 AB12345 AB12345-R… id-4   RUS-1     36 YEARS M     BLAC… HISPA… RUS     N    
#>  9 AB12345 AB12345-R… id-6   RUS-1     36 YEARS F     ASIAN NOT H… RUS     Y    
#> 10 AB12345 AB12345-B… id-9   BRA-1     35 YEARS F     BLAC… NOT H… BRA     N    
#> # … with 33 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> #   ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, REGION1 <fct>,
#> #   STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>, BMRKR2 <fct>, ITTFL <fct>,
#> #   SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>, RANDDT <date>, TRTSDTM <dttm>,
#> #   TRTEDTM <dttm>, EOSSTT <fct>, EOTSTT <fct>, EOSDT <date>, EOSDY <int>,
#> #   DCSREAS <fct>, DTHDT <date>, DTHCAUS <fct>, DTHCAT <fct>, LDDTHELD <int>,
#> #   LDDTHGR1 <fct>, LSTALVDT <date>, DTHADY <int>, study_duration_secs <dbl>
radsl(
  N = 10, seed = 1,
  na_percentage = 0.1,
  na_vars = list(
    DTHDT = c(seed = 1234, percentage = 0.1),
    LSTALVDT = c(seed = 1234, percentage = 0.1)
  )
)
#> # A data frame: 10 × 44
#>    STUDYID USUBJID    SUBJID SITEID   AGE AGEU  SEX   RACE  ETHNIC COUNTRY DTHFL
#>    <chr>   <chr>      <chr>  <chr>  <int> <fct> <fct> <fct> <fct>  <fct>   <fct>
#>  1 AB12345 AB12345-C… id-10  CHN-3     35 YEARS M     ASIAN NOT H… CHN     N    
#>  2 AB12345 AB12345-J… id-7   JPN-4     30 YEARS F     ASIAN NOT H… JPN     N    
#>  3 AB12345 AB12345-U… id-3   USA-13    35 YEARS F     AMER… NOT H… USA     N    
#>  4 AB12345 AB12345-B… id-8   BRA-9     31 YEARS F     ASIAN NOT H… BRA     N    
#>  5 AB12345 AB12345-C… id-2   CHN-11    35 YEARS M     BLAC… NOT H… CHN     Y    
#>  6 AB12345 AB12345-C… id-1   CHN-11    35 YEARS F     WHITE UNKNO… CHN     N    
#>  7 AB12345 AB12345-C… id-5   CHN-3     36 YEARS F     ASIAN NOT H… CHN     N    
#>  8 AB12345 AB12345-R… id-4   RUS-1     36 YEARS M     BLAC… HISPA… RUS     N    
#>  9 AB12345 AB12345-R… id-6   RUS-1     36 YEARS F     ASIAN NOT H… RUS     Y    
#> 10 AB12345 AB12345-B… id-9   BRA-1     35 YEARS F     BLAC… NOT H… BRA     N    
#> # … with 33 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> #   ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, REGION1 <fct>,
#> #   STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>, BMRKR2 <fct>, ITTFL <fct>,
#> #   SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>, RANDDT <date>, TRTSDTM <dttm>,
#> #   TRTEDTM <dttm>, EOSSTT <fct>, EOTSTT <fct>, EOSDT <date>, EOSDY <int>,
#> #   DCSREAS <fct>, DTHDT <date>, DTHCAUS <fct>, DTHCAT <fct>, LDDTHELD <int>,
#> #   LDDTHGR1 <fct>, LSTALVDT <date>, DTHADY <int>, study_duration_secs <dbl>
radsl(N = 10, seed = 1, na_percentage = .1)
#> # A data frame: 10 × 44
#>    STUDYID USUBJID    SUBJID SITEID   AGE AGEU  SEX   RACE  ETHNIC COUNTRY DTHFL
#>    <chr>   <chr>      <chr>  <chr>  <int> <fct> <fct> <fct> <fct>  <fct>   <fct>
#>  1 AB12345 AB12345-C… id-10  CHN-3     35 YEARS M     ASIAN NOT H… CHN     N    
#>  2 AB12345 AB12345-J… id-7   JPN-4     30 YEARS F     ASIAN NOT H… JPN     N    
#>  3 AB12345 AB12345-U… id-3   USA-13    NA YEARS NA    AMER… NOT H… USA     N    
#>  4 AB12345 AB12345-B… id-8   BRA-9     31 YEARS F     ASIAN NOT H… BRA     N    
#>  5 AB12345 AB12345-C… id-2   CHN-11    35 YEARS M     BLAC… NOT H… CHN     Y    
#>  6 AB12345 AB12345-C… id-1   CHN-11    35 YEARS F     WHITE UNKNO… CHN     N    
#>  7 AB12345 AB12345-C… id-5   CHN-3     36 YEARS F     ASIAN NOT H… CHN     N    
#>  8 AB12345 AB12345-R… id-4   RUS-1     36 YEARS M     BLAC… HISPA… RUS     N    
#>  9 AB12345 AB12345-R… id-6   RUS-1     36 YEARS F     NA    NOT H… RUS     Y    
#> 10 AB12345 AB12345-B… id-9   BRA-1     35 YEARS F     BLAC… NOT H… BRA     N    
#> # … with 33 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> #   ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, REGION1 <fct>,
#> #   STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>, BMRKR2 <fct>, ITTFL <fct>,
#> #   SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>, RANDDT <date>, TRTSDTM <dttm>,
#> #   TRTEDTM <dttm>, EOSSTT <fct>, EOTSTT <fct>, EOSDT <date>, EOSDY <int>,
#> #   DCSREAS <fct>, DTHDT <date>, DTHCAUS <fct>, DTHCAT <fct>, LDDTHELD <int>,
#> #   LDDTHGR1 <fct>, LSTALVDT <date>, DTHADY <int>, study_duration_secs <dbl>