Description
Support Technical Processes Following 'Maelstrom Research' Standards.
Description
Functions to support rigorous processes in data cleaning, evaluation, and documentation across datasets from different studies based on Maelstrom Research guidelines. The package includes the core functions to evaluate and format the main inputs that define the process, diagnose errors, and summarize and evaluate datasets and their associated data dictionaries. The main outputs are clean datasets and associated metadata, and tabular and visual summary reports. As described in Maelstrom Research guidelines for rigorous retrospective data harmonization (Fortier I and al. (2017) <doi:10.1093/ije/dyw075>).
README.md
madshapR
The madshapR package provides functions for efficient data cleaning, evaluation, and documentation across different datasets. It was developed to support work at Maelstrom Research and includes functions to evaluate and summarize datasets and their associated data dictionaries, identify potential issues in content and structure, and prepare datasets and metadata for further processing. The key outputs provided by the functions are formatted datasets, standardized metadata, and tabular and visual summary reports.
Get started
Install the package
# To install madshapR:
install.packages('madshapR')
library(madshapR)
# If you need help with the package, please use:
madshapR_website()
# Downloadable templates are available here
madshapR_templates()
# Demo files are available here, along with an online demonstration process
madshapR_DEMO