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Hazards, Causality, and Practical Relevance of Collider Effects - Comment on Beyersmann et al. "Hazards Constitute
Ralf Bender1,2, Lars Beckmann1
1Department of Medical Biometry, Institute for Quality and Efficiency in Health Care (IQWiG), Cologne, Germany.
Biometrical Journal. Biometrische Zeitschrift
|September 8, 2025
Summary
The hazard ratio, crucial for time-to-event analysis, offers a valid causal interpretation at the population level. Real-world randomized trials typically avoid theoretical issues related to heterogeneity.
Area of Science:
- Biostatistics
- Epidemiology
- Survival Analysis
Background:
- Hazards are fundamental in time-to-event data analysis.
- The interpretation of hazard ratios depends on viewing the hazard function over time.
Purpose of the Study:
- To highlight the causal interpretability of hazard ratios as population-level estimands.
- To discuss the practical avoidance of theoretical issues like strong heterogeneity in randomized controlled trials.
Main Methods:
- Conceptual analysis of hazard functions and hazard ratios.
- Review of empirical evidence from randomized controlled trials.
Main Results:
- The hazard ratio serves as a valid population-level causal estimand.
- Theoretical problems arising from heterogeneity are generally not observed in practice.
Conclusions:
- The hazard ratio is a robust measure with causal validity for population-level inference.
- Randomized controlled trials effectively manage potential confounding factors, ensuring reliable hazard ratio interpretation.
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