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siera

Overview

With siera, users ingest Analysis Results Standard (ARS) metadata and auto-generate R scripts that, when run with corresponding ADaM datasets, provide Analysis Results Datasets (ARDs).

The CDISC Analysis Results Standard is a foundational standard that facilitates automation, reproducibility, reusability and traceability of analysis results data.

ARS metadata is officially represented using JSON format (though there is also an Excel representation for easier readability, but the JSON format is recommended for official ARS usage). Such a JSON file contains all relevant metadata to be able to calculate the Analysis Results for a specific Reporting Event. This metadata includes (but is not limited to):

  • Analysis Sets (e.g. SAFFL = “Y”)
  • AnalysisGroupings (e.g. group by Treatment)
  • DataSubsets (e.g. filter by Treatment-Emergent Adverse Events)
  • AnalysisMethods (e.g. calculate ‘n’, ‘Mean’, ‘Min’, ‘Max’, ‘Q1’, ‘Q3’)

Applying all these concepts to ADaM input data, yields Analysis Results in Dataset format (ARDs).

The siera pipeline: ARS metadata is read by readARS(), which writes one R script per output; each script runs against ADaM datasets to produce an ARD.
The siera pipeline: ARS metadata is read by readARS(), which writes one R script per output; each script runs against ADaM datasets to produce an ARD.

Within the pharmaverse ecosystem, siera sits between ARS metadata and the cards package: ADaM datasets are typically built with admiral, siera generates the cards/cardx code that computes the ARD, and packages such as gtsummary and tfrmt turn that ARD into final tables.

Installation

siera can be installed from CRAN with:

The development version can be installed from Github using

devtools::install_github("clymbclinical/siera")

Usage

The siera package has one main function, called readARS. This function takes ARS metadata as input (either JSON or xlsx format), and makes use of the various metadata pieces to populate R scripts, which an be run as-is to produce ARDs. One R script is created for each output (table) as defined in the ARS metadata for the reportingg event.

In order to make use of this function, the following are required as arguments:

  1. A functional ARS file, representing ARS Metadata for a Reporting Event (JSON or xlsx)
  2. An output directory where the R scripts will be placed
  3. A folder containing the related ADaM datasets for the ARDs to be generated, supplied as either CSV (.csv) or SAS transport (.xpt) files

siera picks the reader for each ADaM dataset from its file extension — .csv files are read with readr::read_csv() and .xpt files with haven::read_xpt() — just as the ARS input format is inferred from .json vs .xlsx. No extra argument is needed.

JSON is the recommended ARS representation. If you have an ARS Excel workbook, ars_xlsx_to_json() converts it to a faithful ARS JSON file (an R-native equivalent of CDISC’s excel2ars.py) that can then be passed to readARS().

See the Getting Started vignette for examples and more detail on the process.

More info: