Create a new object of CDISCTealDataset class
cdisc_dataset.Rd![[Stable]](figures/lifecycle-stable.svg)
Function that creates CDISCTealDataset object
Usage
cdisc_dataset(
dataname,
x,
keys = get_cdisc_keys(dataname),
parent = if (identical(dataname, "ADSL")) character(0) else "ADSL",
label = data_label(x),
code = character(0),
vars = list(),
metadata = NULL
)Arguments
- dataname
(
character) a given name for the dataset, it cannot contain spaces- x
(
data.frameorMultiAssayExperiment) object from which the dataset will be created- keys
optional, (
character) vector with primary keys- parent
(
character, optional) parent dataset name- label
(
character) label to describe the dataset- code
(
character) a character string defining the code needed to produce the data set inx- vars
(named
list) in case when this object code depends on otherTealDatasetobject(s) or other constant value, this/these object(s) should be included as named element(s) of the list. For example if this object code needsADSLobject we should specifyvars = list(ADSL = <adsl object>). It's recommended to includeTealDatasetorTealDatasetConnectorobjects to thevarslist to preserve reproducibility. Please note thatvarsare included to this object as localvarsand they cannot be modified within another dataset.- metadata
(named
listorNULL) field containing metadata about the dataset. Each element of the list should be atomic and length one.
Examples
library(scda)
ADSL <- synthetic_cdisc_data("latest")$adsl
cdisc_dataset("ADSL", ADSL, metadata = list(type = "scda", date = "latest"))
#> 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>