Abstract
Many studies in arthroplasty research are based on nonrandomized, retrospective, registry-based cohorts. In these types of studies, patients belonging to different treatment or exposure groups often differ with respect to patient characteristics, medical histories, surgical indications, or other factors. Consequently, comparisons of nonrandomized groups are often subject to treatment selection bias and confounding. Propensity scores can be used to balance cohort characteristics, thus helping to minimize potential bias and confounding. This article explains how propensity scores are created and describes multiple ways in which they can be applied in the analysis of nonrandomized studies. Please visit the following (https://www.youtube.com/watch?v=sqgxl_nZWS4&t=3s) for a video that explains the highlights of the paper in practical terms.
Original language | English (US) |
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Pages (from-to) | 622-626 |
Number of pages | 5 |
Journal | Journal of Arthroplasty |
Volume | 38 |
Issue number | 4 |
DOIs | |
State | Published - Apr 2023 |
Keywords
- bias
- confounding
- inverse probability of treatment
- propensity score
- statistics
- total joint arthroplasty
ASJC Scopus subject areas
- Orthopedics and Sports Medicine