Reads a study folder: SAS transport (.xpt) and SAS (.sas7bdat) files,
Dataset-JSON (.json, .ndjson), or a USDM study document, plus a
Define-XML when one is there. A CORE test-case data/ folder
(_variables.csv and one CSV per dataset) is read too. All of them come out
in the same internal representation, so the evaluator never has to know
which one it got.
Arguments
- path
Directory path.
- usdm
Read a USDM study design document.
FALSEby default: USDM is not what most studies are checked for, and some of its rules take minutes on one file, so it has to be asked for. Without it, a folder holding only a USDM document is refused with a message saying so, never read as empty.
Value
A study object: list(datasets = <named list of domain -> list(data, meta, label)>, define, ct = NULL, standard = list(product, version)). define is the parsed Define-XML if one was
found in path and the xml2 package is installed, and NULL
otherwise; ct is always NULL. Each data is a
data.table::data.table();
each meta is a data.table with columns variable, label, type;
label is the dataset's own label (e.g. "Adverse Events"), or NA if
unavailable. standard is the study's declared standard/version (e.g.
list(product = "SDTMIG", version = "3-4")), read from a CORE test
case's .env file or a USDM document, and both NA for a folder of
datasets, which does not declare one.
Details
Character columns use "" for blank/missing (never NA) to match how
SAS XPT round-trips blanks; numeric columns use NA. Column types are
taken from the source (XPT's own types, or _variables.csv's declared
Char/Num) rather than guessed from the data, so numeric-looking
identifiers (e.g. "007") are never silently coerced.
Examples
dir <- tempfile("coreval_study_")
dir.create(dir)
haven::write_xpt(data.frame(USUBJID = c("1", "2"), AGE = c(30, 65)), file.path(dir, "dm.xpt"))
study <- read_study(dir)
study$datasets$DM$data
#> USUBJID AGE
#> <char> <num>
#> 1: 1 30
#> 2: 2 65
unlink(dir, recursive = TRUE)