Subject-Level Analysis Dataset (ADSL)
radsl.Rd
The Subject-Level Analysis Dataset (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.
Arguments
- N
(
numeric
)
Number of patients.- study_duration
(
numeric
)
Duration of study in years.- seed
(
numeric
)
Seed to use for reproducible random number generation.- with_trt02
(
logical
)
Should period 2 be added.- na_percentage
(
proportion
)
Default percentage of values to be replaced byNA
.- na_vars
(
list
)
A named list where the name of each element is a column name ofds
. Each element of this list should be a numeric vector with two elements:seed
(numeric
)
The seed to be used for this element - can beNA
.percentage
(proportion
)
Percentage of elements to be replaced withNA
. IfNA
,na_percentage
is used as a default.
- ae_withdrawal_prob
(
proportion
)
Probability that there is at least one Adverse Event leading to the withdrawal of a study drug.- cached
boolean whether the cached ADSL data
cadsl
should be returned or new data should be generated. If set toTRUE
then the other arguments toradsl
will be ignored.
Examples
library(random.cdisc.data)
adsl <- radsl(N = 10, study_duration = 2, seed = 1)
adsl
#> # A tibble: 10 × 55
#> 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 Y
#> 5 AB12345 AB12345-C… id-2 CHN-11 35 YEARS M BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-C… id-1 CHN-11 35 YEARS F WHITE NOT H… CHN Y
#> 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… NOT H… RUS N
#> 9 AB12345 AB12345-R… id-6 RUS-1 36 YEARS F ASIAN NOT H… RUS N
#> 10 AB12345 AB12345-B… id-9 BRA-1 35 YEARS F BLAC… UNKNO… BRA N
#> # ℹ 44 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> # ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, TRT02P <fct>,
#> # TRT02A <fct>, REGION1 <fct>, STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>,
#> # BMRKR2 <fct>, ITTFL <fct>, SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>,
#> # AEWITHFL <fct>, RANDDT <date>, TRTSDTM <dttm>, TRTEDTM <dttm>,
#> # TRT01SDTM <dttm>, TRT01EDTM <dttm>, TRT02SDTM <dttm>, TRT02EDTM <dttm>,
#> # AP01SDTM <dttm>, AP01EDTM <dttm>, AP02SDTM <dttm>, AP02EDTM <dttm>, …
adsl <- 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)
)
)
adsl
#> # A data frame: 10 × 55
#> 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 Y
#> 5 AB12345 AB12345-C… id-2 CHN-11 35 YEARS M BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-C… id-1 CHN-11 35 YEARS F WHITE NOT H… CHN Y
#> 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… NOT H… RUS N
#> 9 AB12345 AB12345-R… id-6 RUS-1 36 YEARS F ASIAN NOT H… RUS N
#> 10 AB12345 AB12345-B… id-9 BRA-1 35 YEARS F BLAC… UNKNO… BRA N
#> # ℹ 44 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> # ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, TRT02P <fct>,
#> # TRT02A <fct>, REGION1 <fct>, STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>,
#> # BMRKR2 <fct>, ITTFL <fct>, SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>,
#> # AEWITHFL <fct>, RANDDT <date>, TRTSDTM <dttm>, TRTEDTM <dttm>,
#> # TRT01SDTM <dttm>, TRT01EDTM <dttm>, TRT02SDTM <dttm>, TRT02EDTM <dttm>,
#> # AP01SDTM <dttm>, AP01EDTM <dttm>, AP02SDTM <dttm>, AP02EDTM <dttm>, …
adsl <- radsl(N = 10, seed = 1, na_percentage = .1)
adsl
#> # A data frame: 10 × 55
#> 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 NA YEARS M NA NOT H… CHN N
#> 2 AB12345 AB12345-J… id-7 JPN-4 30 YEARS NA 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 Y
#> 5 AB12345 AB12345-C… id-2 CHN-11 35 YEARS M BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-C… id-1 CHN-11 35 YEARS F WHITE NOT H… CHN Y
#> 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… NOT H… RUS N
#> 9 AB12345 AB12345-R… id-6 RUS-1 36 YEARS F ASIAN NOT H… RUS N
#> 10 AB12345 AB12345-B… id-9 BRA-1 35 YEARS F BLAC… UNKNO… BRA N
#> # ℹ 44 more variables: INVID <chr>, INVNAM <chr>, ARM <fct>, ARMCD <fct>,
#> # ACTARM <fct>, ACTARMCD <fct>, TRT01P <fct>, TRT01A <fct>, TRT02P <fct>,
#> # TRT02A <fct>, REGION1 <fct>, STRATA1 <fct>, STRATA2 <fct>, BMRKR1 <dbl>,
#> # BMRKR2 <fct>, ITTFL <fct>, SAFFL <fct>, BMEASIFL <fct>, BEP01FL <fct>,
#> # AEWITHFL <fct>, RANDDT <date>, TRTSDTM <dttm>, TRTEDTM <dttm>,
#> # TRT01SDTM <dttm>, TRT01EDTM <dttm>, TRT02SDTM <dttm>, TRT02EDTM <dttm>,
#> # AP01SDTM <dttm>, AP01EDTM <dttm>, AP02SDTM <dttm>, AP02EDTM <dttm>, …