How to Distinguish Correlation from Causation in Orthopaedic Research

Correlations in observational studies are commonly misinterpreted as causation. Although correlation is necessary to establish a causal relationship between two variables, correlations may also arise due to chance, reverse causality, or confounding. There are several methods available to orthopaedic researchers to determine whether
the observed correlations are causal. These methods depend on the key components of the study including but not limited to study design and data availability on confounders. In this paper, we illustrate the main concepts surrounding correlation and causation using intuitive real-world examples from the orthopaedic literature. Please visit AJRRC.org to learn more about our program.

Acknowledgements
Funding: This work was funded by a grant from the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) grant P30AR76312 and the American Joint Replacement Research-Collaborative (AJRR-C). The content is solely the responsibility of the authors and does not necessarily
represent the official views of the National Institutes of Health. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. The corresponding
author had full access to all the data in the study, and all authors had final responsibility for the decision
to submit for publication.

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