r-Rmonize

Description

Tools for Data Harmonization.

Description

Integrated tools to support rigorous and well documented data harmonization based on Maelstrom Research guidelines. The package includes functions to assess and prepare input elements, apply specified processing rules to generate harmonized datasets, validate data processing and identify processing errors, and document and summarize harmonized outputs. The harmonization process is defined and structured by two key user-generated documents: the DataSchema (specifying the list of harmonized variables to generate across datasets) and the Data Processing Elements (specifying the input elements and processing algorithms to generate harmonized variables in DataSchema formats). The package was developed to address key challenges of retrospective data harmonization in epidemiology (as described in Fortier I and al. (2017) <doi:10.1093/ije/dyw075>) but can be used for any data harmonization initiative.

README.md

cran.r-project.org

Tools for Data Harmonization

Harmonizing data (achieving or improving inferential equivalence of data collected by separate studies) can be required in epidemiological research but is methodologically and technically challenging. Data collected by separate studies are typically heterogenous, and decisions on if and how to process data must be made, executed accurately, and documented in a transparent manner. Rmonize is an R package developed by Maelstrom Research to address some of the key challenges in this process and facilitate streamlined, reusable, and well documented harmonization pipelines.

Get an overview of processing with Rmonize and links to resources available for each step on the Process page.

For a quick start to using the package, see the vignettes Install your working environment and a Simple example of data processing with Rmonize.

The Glossary provides information about package terminology, and the Functions page provides technical documentation on package functions and built-in materials.

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