coreval (version 0.1.0)

read_study: Read a study into coreval's internal representation

Description

Detects whether path is a directory of XPT datasets (a real study) or a CORE test-case data/ directory (_variables.csv + one CSV per dataset, usually also .env and _datasets.csv), and reads either into the same internal representation, so the evaluator never has to know which one it got.

Usage

read_study(path)

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 (controlled terminology is not bundled). 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 - both NA for a real XPT-based study (no .env).

Arguments

path

Directory path.

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
unlink(dir, recursive = TRUE)