ArticleBMC medical research methodology2025
Propensity Score Matching: should we use it in designing observational studies?
Article in BMC medical research methodology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.
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Who cites it
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance of propensity score methods in observational studies: a systematic review.Systematic reviews · 2026Pooled it
- Clinical outcomes and patient-reported joint noise after total knee arthroplasty using saddle-shaped rotating-platform and bi-cruciate-stabilized implant-surgical systems: a propensity score-matched cohort study.Arthroplasty (London, England) · 2026Article
- Estimating Causal Effects of Malaria Infection on Anaemia Among Children Under Five Years in Uganda: Evidence From a Cross-Sectional Malaria Indicator Survey.Health science reports · 2026Article
- How Are We Matching in ACL Reconstruction Research? A Systematic Review of Methods, Reporting, and Covariate Selection.Orthopaedic journal of sports medicine · 2026Review
- Evaluating the Association of Surgical Setting With Costs and Complications in Ankle Arthrodesis: Medicare Claims Analysis.Foot & ankle orthopaedics · 2026Article
- Examining prosocial tendencies in men who have sex with men: Potential impacts on blood donation following the 2023 reform.Vox sanguinis · 2026Article
- Superior Cerebrovascular Outcomes with Tirzepatide Versus Semaglutide: A Call for Cautious Interpretation of Observational Data.Cardiovascular drugs and therapy · 2026Article
- Post-matching analysis after coarsened exact matching: implications of coarsening for residual confounding and model dependence.Research square · 2026Article
- Examining the Efficacy of Coarsened Exact Matching as an Alternative to Propensity Score Matching.Statistics in medicine · 2026Article
- Article
- Digital cardiac rehabilitation versus traditional cardiac rehabilitation in improving health parameters, patient satisfaction and adherence to guidelines-a systematic review and a meta-analysis.Cardiovascular diagnosis and therapy · 2026Article
- Comparison of emergence agitation between tracheal tube and laryngeal mask airway in pediatric ophthalmic surgery: a propensity-score matching analysis.Frontiers in medicine · 2026Article
- Branched-Chain Amino Acid Supplementation and Clinical Outcomes in Liver Cirrhosis: A Propensity Score-Matched Multicenter Retrospective Cohort Study.Digestive diseases and sciences · 2026Article
- Effect of Remimazolam versus Propofol Sedation on Postoperative Sleep Quality Following Gastroscopy: A Propensity Score-Matched Cohort Study.Drug design, development and therapy · 2026Article
- Is propensity score matching still a valid design choice for surgical comparative effectiveness research?The Journal of thoracic and cardiovascular surgery · 2026Article
- The Multidimensional Burden of COPD in China: A Propensity Score-Matched Comparison with Other Prevalent Non-Communicable Diseases.International journal of chronic obstructive pulmonary disease · 2026Article
- Article
- Association of Glucagon-like Peptide-1 Receptor Agonists with Mortality and Aspiration Pneumonia in Patients with Type 2 Diabetes After Gastrostomy: A Target Trial Emulation Study.International journal of medical sciences · 2026Article
- Beyond chronological age: a decision tree model integrating nutritional and renal function indicators for risk prediction in pre-frail older adults with hepatolithiasis.Frontiers in medicine · 2026Article
- History of Pulmonary Tuberculosis Accelerates Early Onset and Severity of COPD: Evidence from a Multicenter Study in Romania.Journal of clinical medicine · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPropensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data. In a valid PSM design where all baseline confounders are measured and matched, the confounders would be balanced, allowing the treatment status to be considered as if it were randomly assigned. Nevertheless, recent research has unveiled a different facet of PSM, termed "the PSM paradox". As PSM approaches exact matching by progressively pruning matched sets in order of decreasing propensity score distance, it can paradoxically lead to greater covariate imbalance, heightened model dependence, and increased bias, contrary to its intended purpose.
methodsWe used analytic formula, simulation, and literature to demonstrate that this paradox stems from the misuse of metrics for assessing chance imbalance and bias.
resultsFirstly, matched pairs typically exhibit different covariate values despite having identical propensity scores. However, this disparity represents a "chance" difference and will average to zero over a large number of matched pairs. Common distance metrics cannot capture this "chance" nature in covariate imbalance, instead reflecting increasing variability in chance imbalance as units are pruned and the sample size diminishes. Secondly, the largest estimate among numerous fitted models, because of uncertainty among researchers over the correct model, was used to determine statistical bias. This cherry-picking procedure ignores the most significant benefit of matching design-reducing model dependence based on its robustness against model misspecification bias.
conclusionsWe conclude that the PSM paradox is not a legitimate concern and should not stop researchers from using PSM designs.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.