![[Stable]](figures/lifecycle-stable.svg)
Usage
get_datasets(x)
# S3 method for TealDataAbstract
get_datasets(x)
# S3 method for TealDatasetConnector
get_datasets(x)
# S3 method for TealDataset
get_datasets(x)Arguments
- x
(
TealData)
object containing datasets.
Examples
# TealData --------
library(scda)
adsl <- cdisc_dataset(
dataname = "ADSL",
x = synthetic_cdisc_data("latest")$adsl,
code = "library(scda)\nADSL <- synthetic_cdisc_data(\"latest\")$adsl"
)
adae <- cdisc_dataset(
dataname = "ADAE",
x = synthetic_cdisc_data("latest")$adae,
code = "library(scda)\nADTTE <- synthetic_cdisc_data(\"latest\")$adae"
)
rd <- cdisc_data(adsl, adae)
get_datasets(rd)
#> $ADSL
#> A CDISCTealDataset object containing the following data.frame (400 rows and 44 columns):
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX
#> 1 AB12345 AB12345-CHN-3-id-128 id-128 CHN-3 32 YEARS M
#> 2 AB12345 AB12345-CHN-15-id-262 id-262 CHN-15 35 YEARS M
#> 3 AB12345 AB12345-RUS-3-id-378 id-378 RUS-3 30 YEARS F
#> 4 AB12345 AB12345-CHN-11-id-220 id-220 CHN-11 26 YEARS F
#> 5 AB12345 AB12345-CHN-7-id-267 id-267 CHN-7 40 YEARS M
#> 6 AB12345 AB12345-CHN-15-id-201 id-201 CHN-15 49 YEARS M
#> RACE ETHNIC COUNTRY DTHFL INVID
#> 1 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-3
#> 2 BLACK OR AFRICAN AMERICAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> 3 ASIAN NOT HISPANIC OR LATINO RUS N INV ID RUS-3
#> 4 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-11
#> 5 ASIAN UNKNOWN CHN N INV ID CHN-7
#> 6 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> INVNAM ARM ARMCD ACTARM ACTARMCD TRT01P
#> 1 Dr. CHN-3 Doe A: Drug X ARM A A: Drug X ARM A A: Drug X
#> 2 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 3 Dr. RUS-3 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 4 Dr. CHN-11 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 5 Dr. CHN-7 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 6 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> TRT01A REGION1 STRATA1 STRATA2 BMRKR1 BMRKR2 ITTFL SAFFL BMEASIFL
#> 1 A: Drug X Asia C S2 14.424934 MEDIUM Y Y Y
#> 2 C: Combination Asia C S1 4.055463 LOW Y Y N
#> 3 C: Combination Eurasia A S1 2.803240 HIGH Y Y Y
#> 4 B: Placebo Asia B S2 10.262734 MEDIUM Y Y Y
#> 5 B: Placebo Asia C S1 6.206763 LOW Y Y N
#> 6 C: Combination Asia C S2 6.906799 MEDIUM Y Y Y
#> BEP01FL RANDDT TRTSDTM TRTEDTM EOSSTT
#> 1 Y 2019-02-22 2019-02-24 11:09:18 2021-02-23 22:47:42 COMPLETED
#> 2 N 2019-02-26 2019-02-26 09:05:00 2021-02-25 20:43:24 COMPLETED
#> 3 N 2019-02-24 2019-02-28 03:19:08 2021-02-27 14:57:32 COMPLETED
#> 4 Y 2019-02-27 2019-03-01 13:33:03 2021-03-01 01:11:27 COMPLETED
#> 5 N 2019-03-01 2019-03-02 00:09:16 2021-03-01 11:47:40 COMPLETED
#> 6 N 2019-03-05 2019-03-05 15:23:44 2021-02-17 20:24:57 DISCONTINUED
#> EOTSTT EOSDT EOSDY DCSREAS DTHDT DTHCAUS DTHCAT LDDTHELD
#> 1 COMPLETED 2021-02-23 731 <NA> <NA> <NA> <NA> NA
#> 2 COMPLETED 2021-02-25 731 <NA> <NA> <NA> <NA> NA
#> 3 COMPLETED 2021-02-27 731 <NA> <NA> <NA> <NA> NA
#> 4 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 5 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 6 DISCONTINUED 2021-02-17 716 LACK OF EFFICACY <NA> <NA> <NA> NA
#> LDDTHGR1 LSTALVDT DTHADY study_duration_secs
#> 1 <NA> 2021-03-05 NA 63113904
#> 2 <NA> 2021-03-15 NA 63113904
#> 3 <NA> 2021-03-15 NA 63113904
#> 4 <NA> 2021-03-17 NA 63113904
#> 5 <NA> 2021-03-25 NA 63113904
#> 6 <NA> 2021-03-01 NA 63113904
#>
#> ...
#> # A tibble: 6 × 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-CH… id-11 CHN-9 28 YEARS F NATI… HISPA… CHN N
#> 2 AB12345 AB12345-CH… id-352 CHN-16 28 YEARS M ASIAN HISPA… CHN N
#> 3 AB12345 AB12345-CH… id-186 CHN-1 27 YEARS M ASIAN NOT H… CHN N
#> 4 AB12345 AB12345-CH… id-371 CHN-1 28 YEARS F ASIAN NOT H… CHN Y
#> 5 AB12345 AB12345-CH… id-233 CHN-1 36 YEARS F BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-US… id-131 USA-12 44 YEARS F AMER… NOT H… USA 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>
#>
#> $ADAE
#> A CDISCTealDataset object containing the following data.frame (1934 rows and 74 columns):
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX RACE
#> 1 AB12345 AB12345-BRA-1-id-134 id-134 BRA-1 47 YEARS M WHITE
#> 2 AB12345 AB12345-BRA-1-id-134 id-134 BRA-1 47 YEARS M WHITE
#> 3 AB12345 AB12345-BRA-1-id-134 id-134 BRA-1 47 YEARS M WHITE
#> 4 AB12345 AB12345-BRA-1-id-134 id-134 BRA-1 47 YEARS M WHITE
#> 5 AB12345 AB12345-BRA-1-id-141 id-141 BRA-1 35 YEARS F WHITE
#> 6 AB12345 AB12345-BRA-1-id-141 id-141 BRA-1 35 YEARS F WHITE
#> ETHNIC COUNTRY DTHFL INVID INVNAM
#> 1 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> 2 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> 3 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> 4 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> 5 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> 6 NOT HISPANIC OR LATINO BRA N INV ID BRA-1 Dr. BRA-1 Doe
#> ARM ARMCD ACTARM ACTARMCD TRT01P TRT01A
#> 1 A: Drug X ARM A A: Drug X ARM A A: Drug X A: Drug X
#> 2 A: Drug X ARM A A: Drug X ARM A A: Drug X A: Drug X
#> 3 A: Drug X ARM A A: Drug X ARM A A: Drug X A: Drug X
#> 4 A: Drug X ARM A A: Drug X ARM A A: Drug X A: Drug X
#> 5 C: Combination ARM C C: Combination ARM C C: Combination C: Combination
#> 6 C: Combination ARM C C: Combination ARM C C: Combination C: Combination
#> REGION1 STRATA1 STRATA2 BMRKR1 BMRKR2 ITTFL SAFFL BMEASIFL BEP01FL
#> 1 South America B S2 6.462991 LOW Y Y Y N
#> 2 South America B S2 6.462991 LOW Y Y Y N
#> 3 South America B S2 6.462991 LOW Y Y Y N
#> 4 South America B S2 6.462991 LOW Y Y Y N
#> 5 South America B S1 7.516076 HIGH Y Y Y Y
#> 6 South America B S1 7.516076 HIGH Y Y Y Y
#> RANDDT TRTSDTM TRTEDTM EOSSTT EOTSTT
#> 1 2020-11-03 2020-11-04 03:50:33 2022-11-04 15:28:57 COMPLETED COMPLETED
#> 2 2020-11-03 2020-11-04 03:50:33 2022-11-04 15:28:57 COMPLETED COMPLETED
#> 3 2020-11-03 2020-11-04 03:50:33 2022-11-04 15:28:57 COMPLETED COMPLETED
#> 4 2020-11-03 2020-11-04 03:50:33 2022-11-04 15:28:57 COMPLETED COMPLETED
#> 5 2020-07-22 2020-07-25 14:10:56 2022-07-26 01:49:20 COMPLETED COMPLETED
#> 6 2020-07-22 2020-07-25 14:10:56 2022-07-26 01:49:20 COMPLETED COMPLETED
#> EOSDT EOSDY DCSREAS DTHDT DTHCAUS DTHCAT LDDTHELD LDDTHGR1 LSTALVDT
#> 1 2022-11-04 731 <NA> <NA> <NA> <NA> NA <NA> 2022-11-15
#> 2 2022-11-04 731 <NA> <NA> <NA> <NA> NA <NA> 2022-11-15
#> 3 2022-11-04 731 <NA> <NA> <NA> <NA> NA <NA> 2022-11-15
#> 4 2022-11-04 731 <NA> <NA> <NA> <NA> NA <NA> 2022-11-15
#> 5 2022-07-26 731 <NA> <NA> <NA> <NA> NA <NA> 2022-08-10
#> 6 2022-07-26 731 <NA> <NA> <NA> <NA> NA <NA> 2022-08-10
#> DTHADY study_duration_secs ASEQ AESEQ AETERM AELLT
#> 1 NA 63113904 1 1 trm B.2.1.2.1 llt B.2.1.2.1
#> 2 NA 63113904 2 2 trm D.1.1.4.2 llt D.1.1.4.2
#> 3 NA 63113904 3 3 trm A.1.1.1.2 llt A.1.1.1.2
#> 4 NA 63113904 4 4 trm A.1.1.1.2 llt A.1.1.1.2
#> 5 NA 63113904 1 1 trm B.2.1.2.1 llt B.2.1.2.1
#> 6 NA 63113904 2 2 trm D.2.1.5.3 llt D.2.1.5.3
#> AEDECOD AEHLT AEHLGT AEBODSYS AESOC AESEV AESER
#> 1 dcd B.2.1.2.1 hlt B.2.1.2 hlgt B.2.1 cl B.2 cl B MODERATE N
#> 2 dcd D.1.1.4.2 hlt D.1.1.4 hlgt D.1.1 cl D.1 cl D MODERATE N
#> 3 dcd A.1.1.1.2 hlt A.1.1.1 hlgt A.1.1 cl A.1 cl A MODERATE Y
#> 4 dcd A.1.1.1.2 hlt A.1.1.1 hlgt A.1.1 cl A.1 cl A MODERATE Y
#> 5 dcd B.2.1.2.1 hlt B.2.1.2 hlgt B.2.1 cl B.2 cl B MODERATE N
#> 6 dcd D.2.1.5.3 hlt D.2.1.5 hlgt D.2.1 cl D.2 cl D MILD N
#> AEACN AEREL AEOUT AESDTH TRTEMFL
#> 1 DOSE NOT CHANGED N RECOVERED/RESOLVED N Y
#> 2 DOSE NOT CHANGED N RECOVERING/RESOLVING N Y
#> 3 DOSE NOT CHANGED N RECOVERED/RESOLVED WITH SEQUELAE N Y
#> 4 DOSE NOT CHANGED N RECOVERING/RESOLVING N Y
#> 5 DOSE INCREASED N RECOVERED/RESOLVED N Y
#> 6 UNKNOWN Y NOT RECOVERED/NOT RESOLVED N Y
#> AECONTRT ASTDTM AENDTM ASTDY AENDY AETOXGR SMQ01NAM SMQ02NAM SMQ01SC
#> 1 N 2021-07-13 2022-04-05 251 517 3 <NA> <NA> <NA>
#> 2 N 2021-09-04 2022-05-16 304 558 3 <NA> <NA> <NA>
#> 3 Y 2022-03-15 2022-10-29 496 724 2 <NA> <NA> <NA>
#> 4 N 2022-07-05 2022-09-08 608 673 2 <NA> <NA> <NA>
#> 5 N 2021-04-10 2021-04-17 259 266 3 <NA> <NA> <NA>
#> 6 Y 2021-05-24 2022-07-18 303 723 1 <NA> <NA> <NA>
#> SMQ02SC CQ01NAM ANL01FL AERELNST
#> 1 <NA> <NA> Y OTHER
#> 2 <NA> <NA> Y DISEASE UNDER STUDY
#> 3 <NA> <NA> Y DISEASE UNDER STUDY
#> 4 <NA> <NA> Y DISEASE UNDER STUDY
#> 5 <NA> <NA> Y NONE
#> 6 <NA> D.2.1.5.3/A.1.1.1.1 AESI Y DISEASE UNDER STUDY
#> AEACNOTH
#> 1 PROCEDURE/SURGERY
#> 2 MEDICATION
#> 3 NONE
#> 4 SUBJECT DISCONTINUED FROM STUDY
#> 5 PROCEDURE/SURGERY
#> 6 PROCEDURE/SURGERY
#>
#> ...
#> # A tibble: 6 × 74
#> 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-US… id-206 USA-8 34 YEARS F ASIAN NOT H… USA N
#> 2 AB12345 AB12345-US… id-206 USA-8 34 YEARS F ASIAN NOT H… USA N
#> 3 AB12345 AB12345-US… id-206 USA-8 34 YEARS F ASIAN NOT H… USA N
#> 4 AB12345 AB12345-US… id-130 USA-9 40 YEARS M ASIAN NOT H… USA N
#> 5 AB12345 AB12345-US… id-130 USA-9 40 YEARS M ASIAN NOT H… USA N
#> 6 AB12345 AB12345-US… id-130 USA-9 40 YEARS M ASIAN NOT H… USA N
#> # … with 63 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>, …
#>
# TealDataConnector --------
adsl_cf <- callable_function(function() synthetic_cdisc_data("latest")$adsl)
adsl <- cdisc_dataset_connector(
dataname = "ADSL",
pull_callable = adsl_cf,
keys = get_cdisc_keys("ADSL")
)
adlb_cf <- callable_function(function() synthetic_cdisc_data("latest")$adlb)
adlb <- cdisc_dataset_connector(
dataname = "ADLB",
pull_callable = adlb_cf,
keys = get_cdisc_keys("ADLB")
)
rdc <- relational_data_connector(
connection = data_connection(),
connectors = list(adsl, adlb)
)
rdc$set_ui(function(id, connection, connectors) p("Example UI"))
rdc$set_server(
function(id, connection, connectors) {
moduleServer(
id = id,
module = function(input, output, session) {
# Note this is simplified as we are not opening a real connection here
for (connector in connectors) {
set_args(connector, args = list(name = input$name))
# pull each dataset
connector$get_server()(id = connector$get_dataname())
if (connector$is_failed()) {
break
}
}
}
)
}
)
if (FALSE) {
load_datasets(rdc)
get_datasets(rdc)
}
# TealData --------
drc <- cdisc_data(rdc, adae)
if (FALSE) {
get_datasets(drc)
}
# TealDatasetConnector --------
library(scda)
adsl_cf <- callable_function(
function() {
synthetic_cdisc_data("latest")$adsl
}
)
rdc <- cdisc_dataset_connector("ADSL", adsl_cf, keys = get_cdisc_keys("ADSL"))
if (FALSE) {
load_datasets(rdc)
get_datasets(rdc)
}
# TealDataset --------
library(scda)
adsl <- cdisc_dataset(
dataname = "ADSL",
x = synthetic_cdisc_data("latest")$adsl,
code = "library(scda)\nADSL <- synthetic_cdisc_data(\"latest\")$adsl"
)
get_datasets(adsl)
#> A CDISCTealDataset object containing the following data.frame (400 rows and 44 columns):
#> STUDYID USUBJID SUBJID SITEID AGE AGEU SEX
#> 1 AB12345 AB12345-CHN-3-id-128 id-128 CHN-3 32 YEARS M
#> 2 AB12345 AB12345-CHN-15-id-262 id-262 CHN-15 35 YEARS M
#> 3 AB12345 AB12345-RUS-3-id-378 id-378 RUS-3 30 YEARS F
#> 4 AB12345 AB12345-CHN-11-id-220 id-220 CHN-11 26 YEARS F
#> 5 AB12345 AB12345-CHN-7-id-267 id-267 CHN-7 40 YEARS M
#> 6 AB12345 AB12345-CHN-15-id-201 id-201 CHN-15 49 YEARS M
#> RACE ETHNIC COUNTRY DTHFL INVID
#> 1 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-3
#> 2 BLACK OR AFRICAN AMERICAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> 3 ASIAN NOT HISPANIC OR LATINO RUS N INV ID RUS-3
#> 4 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-11
#> 5 ASIAN UNKNOWN CHN N INV ID CHN-7
#> 6 ASIAN NOT HISPANIC OR LATINO CHN N INV ID CHN-15
#> INVNAM ARM ARMCD ACTARM ACTARMCD TRT01P
#> 1 Dr. CHN-3 Doe A: Drug X ARM A A: Drug X ARM A A: Drug X
#> 2 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 3 Dr. RUS-3 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> 4 Dr. CHN-11 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 5 Dr. CHN-7 Doe B: Placebo ARM B B: Placebo ARM B B: Placebo
#> 6 Dr. CHN-15 Doe C: Combination ARM C C: Combination ARM C C: Combination
#> TRT01A REGION1 STRATA1 STRATA2 BMRKR1 BMRKR2 ITTFL SAFFL BMEASIFL
#> 1 A: Drug X Asia C S2 14.424934 MEDIUM Y Y Y
#> 2 C: Combination Asia C S1 4.055463 LOW Y Y N
#> 3 C: Combination Eurasia A S1 2.803240 HIGH Y Y Y
#> 4 B: Placebo Asia B S2 10.262734 MEDIUM Y Y Y
#> 5 B: Placebo Asia C S1 6.206763 LOW Y Y N
#> 6 C: Combination Asia C S2 6.906799 MEDIUM Y Y Y
#> BEP01FL RANDDT TRTSDTM TRTEDTM EOSSTT
#> 1 Y 2019-02-22 2019-02-24 11:09:18 2021-02-23 22:47:42 COMPLETED
#> 2 N 2019-02-26 2019-02-26 09:05:00 2021-02-25 20:43:24 COMPLETED
#> 3 N 2019-02-24 2019-02-28 03:19:08 2021-02-27 14:57:32 COMPLETED
#> 4 Y 2019-02-27 2019-03-01 13:33:03 2021-03-01 01:11:27 COMPLETED
#> 5 N 2019-03-01 2019-03-02 00:09:16 2021-03-01 11:47:40 COMPLETED
#> 6 N 2019-03-05 2019-03-05 15:23:44 2021-02-17 20:24:57 DISCONTINUED
#> EOTSTT EOSDT EOSDY DCSREAS DTHDT DTHCAUS DTHCAT LDDTHELD
#> 1 COMPLETED 2021-02-23 731 <NA> <NA> <NA> <NA> NA
#> 2 COMPLETED 2021-02-25 731 <NA> <NA> <NA> <NA> NA
#> 3 COMPLETED 2021-02-27 731 <NA> <NA> <NA> <NA> NA
#> 4 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 5 COMPLETED 2021-03-01 731 <NA> <NA> <NA> <NA> NA
#> 6 DISCONTINUED 2021-02-17 716 LACK OF EFFICACY <NA> <NA> <NA> NA
#> LDDTHGR1 LSTALVDT DTHADY study_duration_secs
#> 1 <NA> 2021-03-05 NA 63113904
#> 2 <NA> 2021-03-15 NA 63113904
#> 3 <NA> 2021-03-15 NA 63113904
#> 4 <NA> 2021-03-17 NA 63113904
#> 5 <NA> 2021-03-25 NA 63113904
#> 6 <NA> 2021-03-01 NA 63113904
#>
#> ...
#> # A tibble: 6 × 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-CH… id-11 CHN-9 28 YEARS F NATI… HISPA… CHN N
#> 2 AB12345 AB12345-CH… id-352 CHN-16 28 YEARS M ASIAN HISPA… CHN N
#> 3 AB12345 AB12345-CH… id-186 CHN-1 27 YEARS M ASIAN NOT H… CHN N
#> 4 AB12345 AB12345-CH… id-371 CHN-1 28 YEARS F ASIAN NOT H… CHN Y
#> 5 AB12345 AB12345-CH… id-233 CHN-1 36 YEARS F BLAC… NOT H… CHN N
#> 6 AB12345 AB12345-US… id-131 USA-12 44 YEARS F AMER… NOT H… USA 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>