Year: 2024
Type: article
Abstract: Quantitative data quality assurance is the systematic process and procedures used to ensure the accuracy, consistency, reliability, and integrity of data throughout the research process. Effective quality assurance helps identify and correct errors, reduce biases, and ensure the data meets the standards needed for analysis and reporting. This paper provides an overview of key issues to consider when working with data and reporting findings.
DOI: 10.1111/jpm.13143
Authors: Paul Slater, Felicity Hasson
Institution: University of Ulster
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $4,650
OpenAlex ID: W4405576663