Related Experiment Video
Updated: Jun 14, 2025

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
Published on: April 18, 2025
psHarmonize: Facilitating reproducible large-scale pre-statistical data harmonization and documentation in R
John J Stephen1, Padraig Carolan1, Amy E Krefman1
1Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
Abstract:
Combining pertinent data from multiple studies can increase the robustness of epidemiological investigations. Effective "pre-statistical" data harmonization is paramount to the streamlined conduct of collective, multi-study analysis. Harmonizing data and documenting decisions about the transformations of variables to a common set of categorical values and measurement scales are time consuming and can be error prone, particularly for numerous studies with large quantities of variables. The psHarmonize R package facilitates harmonization by combining multiple datasets, applying data transformation functions, and creating long and wide harmonized datasets. The user provides transformation instructions in a "harmonization sheet" that includes dataset names, variable names, and coding instructions and centrally tracks all decisions. The package performs harmonization, generates error logs as necessary, and creates summary reports of harmonized data. psHarmonize is poised to serve as a central feature of data preparation for the joint analysis of multiple studies.
More Related Videos
09:57Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
Published on: December 16, 2014
08:03Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
Published on: December 7, 2021
Related Concept Videos
Introduction to R
Interpreting R Charts
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
Statistical Software for Data Analysis and Clinical Trials
Statistical Methods for Analyzing Epidemiological Data
Biostatistics: Overview
Discrete variables are...
Statistical Analysis System (SAS)
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...