mediators. All 3 types of variables are associated with both the exposure (eg, surgery
type, implant type, body mass index) and outcome (eg, complications, revision surgery)
but differ in their temporal ordering. To reduce systematic bias, the decision to
include or exclude a variable in an analysis should be based on the variable’s relationship
with the exposure and outcome for each research question. In this article, we define
3 types of variables with case examples from orthopedic research. Please visit the following for videos that explain the highlights of the article in practical terms.
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Zaniletti I., Devick K.L., Larson D.L., Lewallen D.G., Berry D.J., Maradit Kremers H. P-values and power in orthopedic research: myths and reality. J Arthroplasty. In press.
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Published online: September 05, 2022
Received in revised form:
In Press Journal Pre-Proof
One or more of the authors of this paper have disclosed potential or pertinent conflicts of interest, which may include receipt of payment, either direct or indirect, institutional support, or association with an entity in the biomedical field which may be perceived to have potential conflict of interest with this work. For full disclosure statements refer to https://doi.org/10.1016/j.arth.2022.05.027.
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.
© 2022 Elsevier Inc. All rights reserved.
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