How Cox models react to a study-specific confounder in a patient-level pooled dataset: random effects better cope with an imbalanced covariate across trials unless baseline hazards differ
| Autor: | Ori Ben-Yehuda, Thomas McAndrew, Paul Jenkins, Aaron Crowley, Mordechai Golomb, Yiran Zhang, Björn Redfors, Gregg W. Stone, Maria Alu, Shmuel Chen, Akiko Maehara, Dominic P. Francese, Gary S. Mintz |
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| Rok vydání: | 2019 |
| Předmět: |
Statistics and Probability
Oncology medicine.medical_specialty Proportional hazards model business.industry Confounding food and beverages Random effects model Clinical trial Internal medicine Covariate medicine Clinical endpoint Statistics Probability and Uncertainty Single trial Baseline (configuration management) business |
| Zdroj: | Journal of Applied Statistics. 46:1903-1916 |
| ISSN: | 1360-0532 0266-4763 |
| Popis: | Combining patient-level data from clinical trials can connect rare phenomena with clinical endpoints, but statistical techniques applied to a single trial may become problematical when trials are p... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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