This function builds a dataset out of the columns that just need to be pulled
through. So any variable that has a derivation in the format of
'dataset.variable' will be pulled through to create the new dataset. When
there are multiple datasets present, they will be joined by the shared
key_seq variables. These columns are often called 'Predecessors' in ADaM,
but this is not universal so that is optional to specify.
Usage
build_from_derived(
metacore,
ds_list,
dataset_name = NULL,
predecessor_only = TRUE,
keep = FALSE
)Arguments
- metacore
metacore object that contains the specifications for the dataset of interest.
- ds_list
Named list of datasets that are needed to build the from. If the list is unnamed,then it will use the names of the objects.
- dataset_name
Optional string to specify the dataset that is being built. This is only needed if the metacore object provided hasn't already been subsetted.
- predecessor_only
By default
TRUE, so only variables with the origin of 'Predecessor' will be used. IfFALSEany derivation matching the dataset.variable will be used.- keep
String to determine which columns from the original datasets should be kept - "FALSE" (default): only columns that are also present in the ADaM specification are kept in the output. - "ALL": all original columns are carried through to the ADaM, including those that have been renamed. e.g. if DM.ARM is a predecessor to DM.TRT01P, both ARM and TRT01P will be present as columns in the ADaM output. - "PREREQUISITE": columns are retained if they are required for future derivations in the specification. Additional prerequisite columns are identified as columns that appear in the 'derivation' column of the metacore object, but not as direct predecessors. Predecessors are defined as columns where the derivation is a 1:1 copy of a column in a source dataset.
e.g. derivation = "VS.VSTESTCD" is a predecessor, while derivation = "Value of VS.VSSTRESN where VS.VSTESTCD == 'Heart Rate'" contains both VS.VSTESTCD and VS.VSSTRESN as prerequisites, and these columns will be kept through to the ADaM.
Examples
library(metacore)
library(haven)
library(magrittr)
load(metacore_example("pilot_ADaM.rda"))
spec <- metacore %>% select_dataset("ADSL")
ds_list <- list(DM = read_xpt(metatools_example("dm.xpt")))
build_from_derived(spec, ds_list, predecessor_only = FALSE)
#> # A tibble: 306 × 14
#> STUDYID USUBJID SUBJID SITEID ARM TRT01P AGE AGEU RACE SEX ETHNIC
#> <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr>
#> 1 CDISCPILOT… 01-701… 1015 701 Plac… Place… 63 YEARS WHITE F HISPA…
#> 2 CDISCPILOT… 01-701… 1023 701 Plac… Place… 64 YEARS WHITE M HISPA…
#> 3 CDISCPILOT… 01-701… 1028 701 Xano… Xanom… 71 YEARS WHITE M NOT H…
#> 4 CDISCPILOT… 01-701… 1033 701 Xano… Xanom… 74 YEARS WHITE M NOT H…
#> 5 CDISCPILOT… 01-701… 1034 701 Xano… Xanom… 77 YEARS WHITE F NOT H…
#> 6 CDISCPILOT… 01-701… 1047 701 Plac… Place… 85 YEARS WHITE F NOT H…
#> 7 CDISCPILOT… 01-701… 1057 701 Scre… Scree… 59 YEARS WHITE F HISPA…
#> 8 CDISCPILOT… 01-701… 1097 701 Xano… Xanom… 68 YEARS WHITE M NOT H…
#> 9 CDISCPILOT… 01-701… 1111 701 Xano… Xanom… 81 YEARS WHITE F NOT H…
#> 10 CDISCPILOT… 01-701… 1115 701 Xano… Xanom… 84 YEARS WHITE M NOT H…
#> # ℹ 296 more rows
#> # ℹ 3 more variables: DTHFL <chr>, RFSTDTC <chr>, RFENDTC <chr>
# Building an ADaM (ADVS) from multiple input datasets, keeping columns
# needed for future transformations
library(metacore)
library(haven)
library(magrittr)
library(safetyData)
load(metacore_example("pilot_ADaM.rda"))
spec <- metacore %>% select_dataset("ADVS")
ds_list <- list("VS" = safetyData::sdtm_vs,"ADSL" = safetyData::adam_adsl)
build_from_derived(spec,
ds_list,
predecessor_only = FALSE,
keep = "PREREQUISITE"
)
#> # A tibble: 29,643 × 27
#> STUDYID SITEID USUBJID AGE AGEGR1 AGEGR1N RACE RACEN SEX SAFFL
#> <chr> <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr> <chr>
#> 1 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 2 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 3 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 4 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 5 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 6 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 7 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 8 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 9 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> 10 CDISCPILOT01 701 01-701-1015 63 <65 1 WHITE 1 F Y
#> # ℹ 29,633 more rows
#> # ℹ 17 more variables: TRTSDT <date>, TRTEDT <date>, TRTP <chr>, TRTPN <dbl>,
#> # TRTA <dbl>, TRTAN <dbl>, PARAMCD <chr>, ADY <int>, ATPT <chr>, AVAL <dbl>,
#> # BASETYPE <chr>, VISITNUM <dbl>, VISIT <chr>, VSSEQ <int>, ABLFL <chr>,
#> # VSDTC <chr>, VSSTRESN <dbl>